/* PROCESS for SPSS v2.10 */. /* Written by Andrew F. Hayes */. /* www.afhayes.com */. /* Copyright 2013 */. /* Read the documentation */. /* available in Appendix A of */. /* Hayes (2013) prior to use */. /* www.guilford.com/p/hayes3 */. /* For proper results, variable */. /* names in data file must be distinct */. /* in the first eight characters */. set printback = off. define bcboot (databcbt = !charend ('/')/estmte = !charend ('/') !default(9999)). compute temp = !databcbt. compute temp(GRADE(!databcbt)) = !databcbt. compute badlo = 0. compute badhi = 0. do if (!estmte <> 9999). compute pv=csum(temp < !estmte)/boot. compute ppv = pv. do if (pv > .5). compute ppv = 1-pv. end if. compute y5=sqrt(-2*ln(ppv)). compute xp=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0). do if (pv <= .5). compute xp = -xp. end if. compute cilow=rnd(boot*(cdfnorm(2*xp+xp2))). compute cihigh=trunc(boot*(cdfnorm(2*xp+(-xp2))))+1. do if (cilow < 1). compute cilow = 1. compute booterr=1. compute badlo = 1. end if. do if (cihigh > boot). compute cihigh = boot. compute booterr=1. compute badhi = 1. end if. compute llcit=temp(cilow,1). compute ulcit=temp(cihigh,1). end if. do if (!estmte = 9999). compute llcit=temp(cilow,1). compute ulcit=temp(cihigh,1). end if. !enddefine. define process (vars = !charend('/')/model = !charend('/') !default(77)/y = !charend('/')/m = !charend('/')/x = !charend ('/') /w = !charend('/') !default(xxx)/z = !charend('/') !default(xxx)/v = !charend('/') !default(xxx)/q = !charend ('/') !default(xxx)/conf = !charend('/') !default(95) /hc3 = !charend('/') !default(0)/cluster = !charend('/') !default(xxx)/wmodval = !charend('/') !default (999)/zmodval = !charend('/') !default(999)/ vmodval = !charend('/') !default (999)/qmodval = !charend('/') !default(999)/mmodval = !charend('/') !default (999)/xmodval = !charend('/') !default (999) /boot = !charend('/') !default(1000)/center = !charend('/') !default(0)/quantile = !charend('/') !default(0)/effsize = !charend('/') !default(0)/normal = !charend('/') !default(0) /varorder = !charend('/') !default(2)/total = !charend('/') !default(0)/plot = !charend('/') !default(0)/detail = !charend('/') !default(1) /iterate = !charend('/') !default(10000)/converge = !charend('/') !default(0.00000001)/percent = !charend('/') !default(0)/jn = !charend('/') !default(0)/ coeffci = !charend('/') !default(1)/covmy = !charend('/') !default(0)/contrast = !charend('/') !default(0)/decimals=!charend('/') !default(F10.4)). set printback=off. string w999999t (A8). string z999999t (A8). string q999999t (A8). string v999999t (A8). compute w999999t = (!quote(!w)). compute z999999t = (!quote(!z)). compute q999999t = (!quote(!q)). compute v999999t = (!quote(!v)). set mxloop = 100000000. set printback = off. matrix. get dat/file = */variables = !vars/names = vnames/missing = 9999. compute ninit = nrow(dat). get dat/file = */variables = !vars/names = vnames/missing = omit. get tmp/file = */variables = !y/names = yname/missing = omit. get tmp/file = */variables = !x/names = xname/missing = omit. get tmp/file = */variables = !m/names = mnames/missing = omit. get tmp/file = */variables = w999999t z999999t v999999t q999999t. compute wname=tmp(1,1). do if (wname = ' '). compute wname = "xxx". end if. compute zname=tmp(1,2). do if (zname = ' '). compute zname = "xxx". end if. compute vname=tmp(1,3). do if (vname = ' '). compute vname = "xxx". end if. compute qname=tmp(1,4). do if (qname = ' '). compute qname = "xxx". end if. compute n = nrow(dat). compute p0=-.322232431088. compute p1 = -1. compute p2 = -.342242088547. compute p3 = -.0204231210245. compute p4 = -.0000453642210148. compute q0 = .0993484626060. compute q1 = .588581570495. compute q2 = .531103462366. compute q3 = .103537752850. compute q4 = .0038560700634. compute badend = 0. compute priorlo = -9999999. compute priorhi = 9999999. compute criterr = 0. compute cluster = 0. compute clsdmy = 0. compute jndich = 0. compute contrast = (!contrast = 1). compute booterr = 0. compute effsize = (!effsize = 1). compute note = make(10,1,0). compute notes = 1. compute iterr = 0. compute clsmtch = 0. compute quantile = (!quantile = 1). compute jn = (!jn = 1). compute wvdich=0. compute mod74dic=0. compute center = (!center = 1). compute detail = (!detail = 1). compute coeffci = (!coeffci = 1). compute conf = !conf. compute bconoff=(!percent <> 1). compute covmy = trunc(!covmy). do if (covmy < 0 or covmy > 2). compute covmy = 0. end if. do if (trunc(conf) ge 100 or (trunc(conf) le 50)). compute conf = 95. compute note(notes,1) = 1. compute notes = notes + 1. end if. do if (n < ninit). compute nmiss = ninit-n. compute note(notes,1) = 11. compute notes = notes + 1. end if. compute errs = 0. compute quantd = {0,0,0,0,0,0}. compute quantc = {0,0,0,0,0,0}. compute mcheck = 0. compute ttt = 0. compute plot = (!plot <> 0). compute runerrs = make(50,1,0). compute model = trunc(!model). print/space=0. do if (jn = 1 and model <> 1 and model <> 3). compute note(notes,1) = 7. compute notes = notes + 1. end if. do if (model > 76) or (model < 1). compute model = 77. compute critterr = 1. compute errs = errs+1. compute runerrs(errs,1) = 19. end if. compute toteff = 0. compute toteff = ((!total = 1)*(!model = 4 or !model = 6)). compute normal = !normal. compute varorder = !varorder. compute hc3 = (!hc3 <> 0). compute clname = !quote(!cluster). compute centvar = {"xxx"}. compute modelm = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1; 0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,2; 0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,3; 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4; 0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,5; 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6; 1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7; 1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,8; 1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9; 1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,10; 1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11; 1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,12; 1,1,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,13; 0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14; 0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,15; 0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,16; 0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,17; 0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,18; 0,0,0,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,19; 0,0,0,1,1,1,0,0,0,1,0,0,0,0,0,0,0,0,20; 1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,21; 1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,22; 1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23; 1,1,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,24; 1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25; 1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,26; 1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,27; 1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,28; 1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,29; 1,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,30; 1,1,0,1,0,0,1,1,0,1,0,0,0,0,0,0,0,0,31; 1,1,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,32; 1,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,0,33; 1,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,34; 1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,35; 1,0,0,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,36; 1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,37; 1,0,0,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,38; 1,0,0,1,1,1,0,0,0,1,0,0,0,0,0,0,0,0,39; 1,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,40; 1,0,0,1,1,0,1,0,0,1,1,0,0,0,0,0,0,0,41; 1,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,42; 1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,43; 1,0,0,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,44; 1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,45; 1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,46; 1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,47; 1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,48; 1,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,49; 1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,50; 1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,51; 1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,52; 1,1,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,53; 1,1,0,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,54; 1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,55; 1,1,1,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,56; 1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,57; 1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,58; 1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,59; 1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,60; 1,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,61; 1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,62; 1,1,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,0,63; 1,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,64; 1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,65; 1,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,0,0,66; 1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,67; 1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,68; 1,1,1,0,0,0,1,1,1,0,0,0,1,0,0,0,0,0,69; 1,0,0,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,70; 1,0,0,1,0,0,1,0,0,1,0,0,1,1,1,0,0,0,71; 1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,72; 1,1,1,0,0,0,1,1,1,0,0,0,1,0,0,1,1,0,73; 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,74; 1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,75; 1,1,0,0,0,0,1,1,0,0,0,0,1,0,0,1,0,0,76; 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,77}. compute wm = modelm(model, 1). compute zm = modelm(model, 2). compute wzm = modelm(model, 3). compute vy = modelm(model, 4). compute qy = modelm(model, 5). compute vqy = modelm(model, 6). compute wy = modelm(model, 7). compute zy = modelm(model, 8). compute wzy = modelm(model, 9). compute vxy = modelm(model, 10). compute qxy = modelm(model, 11). compute vqxy = modelm(model, 12). compute wmy = modelm(model, 13). compute wvmy = modelm(model, 14). compute wvxy = modelm(model, 15). compute zmy = modelm(model,16). compute wzmy = modelm(model,17). compute xmy = modelm(model,18). release modelm. do if (ncol(xname) <> 1). compute errs = errs+1. compute runerrs(errs,1) = 20. compute criterr = 1. end if. do if (ncol(yname) <> 1). compute errs = errs+1. compute runerrs(errs,1) = 21. compute criterr = 1. end if. compute xlist = (wm or zm or wzm or wy or zy or wzy or vxy or qxy or vqxy or wvxy or xmy). compute mlist = (vy or qy or vqy or zmy or wmy or wzmy or xmy or (model < 4)). compute bad = 0. do if (criterr = 0). compute werr = 0. compute verr = 0. compute qerr = 0. compute zerr = 0. compute yerr = 1. compute wlist = (wm or wzm or wy or wzy or wm or wvmy or wvmy or wvxy or wzmy). do if (wlist = 1 and wname = "xxx"). compute werr = 1. compute wlist = 0. compute errs = errs+1. compute runerrs(errs,1) = 4. end if. do if (wlist = 1 and ((wname = qname) or (wname = vname) or (wname = zname) or (wname = xname) or (wname = yname))). compute werr = 4. compute errs = errs+1. compute runerrs(errs,1) = 12). end if. compute zlist = (zm or wzm or zy or wzy or zmy or wzmy). do if (zlist = 1 and zname = "xxx"). compute zerr = 1. compute zlist = 0. compute errs = errs+1. compute runerrs(errs,1) = 5. end if. do if (zlist = 1 and ((zname = qname) or (zname = vname) or (zname = wname) or (zname = xname) or (zname = yname))). compute zerr = 4. compute errs = errs+1. compute runerrs(errs,1) = 13. end if. compute qlist = (qy or vqy or qxy or vqxy). do if (qlist = 1 and qname = "xxx"). compute qerr = 1. compute qlist = 0. compute errs = errs+1. compute runerrs(errs,1) = 6. end if. do if (qlist = 1 and ((qname = zname) or (qname = vname) or (qname = wname) or (qname = xname) or (qname = yname))). compute qerr = 4. compute errs = errs+1. compute runerrs(errs,1) = 14. end if. compute vlist = (vy or vqy or vxy or vqxy or wvmy or wvxy). do if (vlist = 1 and vname = "xxx"). compute verr = 1. compute vlist = 0. compute errs = errs+1. compute runerrs(errs,1) = 7. end if. do if (vlist = 1 and ((vname = zname) or (vname = qname) or (vname = wname) or (vname = xname) or (vname = yname))). compute qerr = 4. compute errs = errs+1. compute runerrs(errs,1) = 15. end if. do if (wlist = 0 and wname <> "xxx"). compute werr = 2. compute errs = errs+1. compute runerrs(errs,1) = 8. end if. do if (zlist = 0 and zname <> "xxx"). compute zerr = 2. compute errs = errs+1. compute runerrs(errs,1) = 9. end if. do if (qlist = 0 and qname <> "xxx"). compute qerr = 2. compute errs = errs+1. compute runerrs(errs,1) = 10. end if. do if (vlist = 0 and vname <> "xxx"). compute verr = 2. compute errs = errs+1. compute runerrs(errs,1) = 11. end if. do if (hc3 = 1). compute note(notes,1) = 3. compute notes = notes+1. end if. compute alpha2 = (1-(conf/100))/2. compute y5=sqrt(-2*ln(alpha2)). compute xp2=-(y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0)). compute cons = make(n,1,1). compute temp = (n*sscp(dat))-(t(csum(dat))*(csum(dat))). compute temp = temp/(n*(n-1)). compute temp = csum(((diag(temp))=0)). do if (temp > 0). compute critterr = 1. compute errs = errs+1. compute runerrs(errs,1) = 27. end if. compute nmeds = ncol(mnames). compute sobel = make(nmeds,4,-999). do if (model = 6 and nmeds > 4). compute errs = errs+1. compute runerrs(errs,1)=2. end if. do if (model < 4 and nmeds > 1). compute errs = errs+1. compute runerrs(errs,1) = 3. end if. compute nmods = (model = 74). compute bad = 0. compute intcnt = 1. compute modvals = 0. compute modvalsd = 0. compute yintemp = {"int_1", "int_2", "int_3", "int_4", "int_5", "int_6", "int_7", "int_8", "int_9", "int_10", "int_11", "int_12", "int_13", "int_14", "int_15"}. compute yintemp = {yintemp, "int_16", "int_17", "int_18", "int_19", "int_20", "int_21", "int_22", "int_23", "int_24", "int_25", "int_26", "int_27", "int_28"}. compute yintemp = {yintemp, "int_29", "int_30", "int_31", "int_32", "int_33", "int_34", "int_35", "int_36", "int_37", "int_38", "int_39", "int_40"}. compute yintemp = {yintemp, "int_41", "int_42", "int_43", "int_44", "int_45", "int_46", "int_47", "int_48", "int_49", "int_50", "int_51", "int_52"}. compute cntname={"(C1)";"(C2)";"(C3)";"(C4)";"(C5)";"(C6)";"(C7)";"(C8)";"(C9)";"(C10)";"(C11)"+ "";"(C12)";"(C13)";"(C14)";"(C15)";"(C16)";"(C17)"}. compute cntname={cntname;"(C18)";"(C19)";"(C20)";"(C21)";"(C22)";"(C23)";"(C24)";"(C25)";"(C26)"+ "";"(C27)";"(C28)";"(C29)";"(C30)";"(C31)"}. compute cntname={cntname;"(C32)";"(C33)";"(C34)";"(C35)";"(C36)";"(C37)";"(C38)";"(C39)";"(C40)"+ "";"(C41)";"(C42)";"(C43)";"(C44)";"(C45)"}. compute cntname={cntname;"(C46)";"(C47)";"(C48)";"(C49)";"(C50)";"(C51)";"(C52)";"(C53)";"(C54)"+ "";"(C55)";"(C56)";"(C57)";"(C58)";"(C59)"}. compute cntname={cntname;"(C60)";"(C61)";"(C62)";"(C63)";"(C64)";"(C65)";"(C66)";"(C67)";"(C68)"+ "";"(C69)";"(C70)";"(C71)";"(C72)";"(C73)"}. compute cntname={cntname;"(C74)";"(C75)";"(C76)";"(C77)";"(C78)";"(C79)";"(C80)";"(C81)";"(C82)"+ "";"(C83)";"(C84)";"(C85)";"(C86)";"(C87)"}. compute cntname={cntname;"(C88)";"(C89)";"(C90)";"(C91)";"(C92)";"(C93)";"(C94)";"(C95)";"(C96)"+ "";"(C97)";"(C98)";"(C99)";"(C100)";"(C101)"}. compute cntname={cntname;"(C102)";"(C103)";"(C104)";"(C105)"}. compute modvnm = {"xxx", "xxx", "xxx", "xxx", "xxx"}. compute modvnm2 = {"xxx", "xxx", "xxx", "xxx", "xxx"}. compute mlab = {" M1 = "; " M2 ="; " M3 ="; " M4 ="; " M5 ="; " M6 ="; " M7 ="; " M8 ="; " M9 ="; " M10 ="}. compute m = make(n,nmeds,1). compute mmat = make(16,nmeds,0). compute ymat = make(8,nmeds,0). compute deco = make(10,1,0). compute modmat = make(5,5,999). compute modmatv = make(1,5,1). compute modmatp = make(1,5,0). compute modprod = modmatv. compute iterate = abs(trunc(!iterate)). compute converge = abs(!converge). compute boot = !boot. compute adjust = 0. do if (boot <> 0). loop. compute cilow = rnd(boot*(1-(conf/100))/2). compute cihigh = trunc((boot*(conf/100)+(boot*(1-(conf/100))/2)))+1. do if (cilow < 1 or cihigh > boot). compute boot=trunc((boot+1000)/1000)*1000. compute adjust = 1. end if. end loop if (cilow gt 0 and cihigh le boot). do if (adjust = 1). compute note(notes,1)=6. compute notes = notes+1. end if. end if. do if (model = 6 and nmeds > 1). compute mmpaths = make((nmeds+2),(nmeds+2),0). do if (nmeds = 2). compute indboot = make(boot+1, 3, 999). else if (nmeds = 3). compute indboot = make(boot+1, 7, 999). else if (nmeds = 4). compute indboot = make(boot+1, 15, 999). end if. compute indlbl = {"Total:"; "Ind1 :"; "Ind2 :"; "Ind3 :"; "Ind4 :"; "Ind5 :"; "Ind6 :"; "Ind7 "+ ":"; "Ind8 :"; "Ind9 :"; "Ind10:"; "Ind11:"; "Ind12:"; "Ind13:"; "Ind14:"; "Ind15:"}. compute indlbl2 = {"Ind1"; "Ind2"; "Ind3"; "Ind4"; "Ind5"; "Ind6"; "Ind7"; "Ind8"; "Ind9"; "Ind10"; "Ind11"; "Ind12"; "Ind13"; "Ind14"; "Ind15"}. compute indces = make(boot+1, 4, 999). end if. do if (model < 4). compute boot = 0. compute cmat = make(10,1,0). compute zmat = make(10,1,0). end if. compute nvarch = make(1,ncol(dat),0). compute wmatch = 0. compute zmatch = 0. compute vmatch = 0. compute qmatch = 0. compute mmatch=0. compute minprobe=0. compute maxprobe=0. loop i = 1 to ncol(vnames). do if (vnames(:,i)=yname). compute y = dat(:,i). compute nvarch(1,i)=1. compute yerr = 0. do if ((yname = xname) or (yname = wname) or (yname = zname) or (yname = vname) or (yname = qname)). compute errs = errs+1. compute runerrs(errs,1)=17. end if. end if. do if (vnames(:,i)=xname). compute x = dat(:,i). compute nvarch(1,i)=1. compute xdich = 1. loop jj = 1 to n. do if ((x(jj,1) <> cmin(x)) and (x(jj,1) <> cmax(x))). compute xdich = 0. break. end if. end loop. compute xmean = csum(x)/n. do if (center = 1 and (model < 4 or xlist > 0)). compute meanvec = make(n,1, xmean). compute x = x-meanvec. compute centvar = {centvar, xname}. end if. compute xmean = csum(x)/n. compute tmp = x-(cons*xmean). compute xsd = sqrt((1/(n-1))*(t(tmp)*tmp)). do if (xdich = 0). compute quantc(1,6) = 1. compute matx = {xmean-xsd; xmean; xmean+xsd}. do if (quantile = 0). do if ((matx(1,1) < cmin(x)) and (model = 74)). compute matx(1,1)=cmin(x). compute minprobe=1. end if. do if ((matx(3,1) > cmax(x)) and (model = 74)). compute matx(3,1)=cmax(x). compute maxprobe=1. end if. end if. do if (quantile = 1). compute quantd(1,6) = 1. compute quantc(1,6) = 0. compute tmp = x. compute tmp(GRADE(x)) = x. compute matx = {tmp(trunc(n*.10),1);tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (xdich = 1). compute matx = {cmin(x); cmax(x)}. do if (model=74). compute matx=cmin(x). compute mod74dic=1. end if. end if. do if (!xmodval <> 999). compute matx = !xmodval. compute quantd(1,6) = 0. compute quantc(1,6) = 0. end if. end if. do if (werr = 0 and wlist = 1). do if (vnames(:,i)=wname). compute werr = 0. compute wmatch = 1. compute w = dat(:,i). do if (center = 1). compute meanvec = make(n,1,csum(w)/n). compute w = w-meanvec. compute centvar = {centvar, wname}. end if. compute nvarch(1,i)=1. compute nmods = nmods + 1. compute wmean = csum(w)/n. compute tmp = w-(cons*wmean). compute wsd = sqrt((1/(n-1))*(t(tmp)*tmp)). compute wdich = 1. loop jj = 1 to n. do if ((w(jj,1) <> cmin(w)) and (w(jj,1) <> cmax(w))). compute wdich = 0. break. end if. end loop. do if (model = 3). compute jndich=wdich. compute jnmin=cmin(w). compute jnmax=cmax(w). end if. do if (wdich = 0). compute matw = {wmean-wsd; wmean; wmean+wsd}. do if (quantile = 0). do if (matw(1,1) < cmin(w)). compute matw(1,1)=cmin(w). compute minprobe=1. end if. do if (matw(3,1) > cmax(w)). compute matw(3,1)=cmax(w). compute maxprobe=1. end if. end if. compute quantc(1,1) = 1. do if (quantile = 1). compute quantd(1,1) = 1. compute quantc(1,1) = 0. compute tmp = w. compute tmp(GRADE(w)) = w. compute matw = {tmp(trunc(n*.10),1);tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (wdich = 1). compute matw = {cmin(w); cmax(w)}. compute wvdich=1. compute cmaxw=cmax(w). compute cminw=cmin(w). end if. do if (!wmodval <> 999). compute matw = !wmodval. compute quantd(1,1) = 0. compute quantc(1,1) = 0. end if. compute modmatv(1,1)=nrow(matw). compute modmat((1:nrow(matw)), 1) = matw. compute modvnm(1,1)=wname. compute modmatp(1,1) = 1. end if. end if. do if (zerr = 0 and zlist = 1). do if (vnames(:,i)=zname). compute zerr = 0. compute zmatch = 1. compute z = dat(:,i). do if (center = 1). compute meanvec = make(n,1,csum(z)/n). compute z = z-meanvec. compute centvar = {centvar, zname}. end if. compute nvarch(1,i)=1. compute nmods = nmods + 1. compute zmean = csum(z)/n. compute tmp = z-(cons*zmean). compute zsd = sqrt((1/(n-1))*(t(tmp)*tmp)). compute zdich = 1. loop jj = 1 to n. do if ((z(jj,1) <> cmin(z)) and (z(jj,1) <> cmax(z))). compute zdich = 0. break. end if. end loop. do if (zdich = 0). compute matz = {zmean-zsd; zmean; zmean+zsd}. do if (quantile = 0). do if (matz(1,1) < cmin(z)). compute matz(1,1)=cmin(z). compute minprobe=1. end if. do if (matz(3,1) > cmax(z)). compute matz(3,1)=cmax(z). compute maxprobe=1. end if. end if. compute quantc(1,2) = 1. do if (quantile = 1). compute quantd(1,2) = 1. compute quantc(1,2) = 0. compute tmp = z. compute tmp(GRADE(z)) = z. compute matz = {tmp(trunc(n*.10),1); tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (zdich = 1). compute matz = {cmin(z); cmax(z)}. end if. do if (!zmodval <> 999). compute matz = !zmodval. compute quantd(1,2) = 0. compute quantc(1,2) = 0. end if. compute modmatv(1,2)=nrow(matz). compute modmat((1:nrow(matz)), 2) = matz. compute modvnm(1,2)=zname. compute modmatp(1,2) = 1. end if. end if. do if (verr = 0 and vlist = 1). do if (vnames(:,i)=vname). compute verr = 0. compute vmatch = 1. compute v = dat(:,i). do if (center = 1). compute meanvec = make(n,1,csum(v)/n). compute v = v-meanvec. compute centvar = {centvar, vname}. end if. compute nvarch(1,i)=1. compute nmods = nmods + 1. compute vmean = csum(v)/n. compute tmp = v-(cons*vmean). compute vsd = sqrt((1/(n-1))*(t(tmp)*tmp)). compute vdich = 1. loop jj = 1 to n. do if ((v(jj,1) <> cmin(v)) and (v(jj,1) <> cmax(v))). compute vdich = 0. break. end if. end loop. do if (vdich = 0). compute matv = {vmean-vsd; vmean; vmean+vsd}. do if (quantile = 0). do if (matv(1,1) < cmin(v)). compute matv(1,1)=cmin(v). compute minprobe=1. end if. do if (matv(3,1) > cmax(v)). compute matv(3,1)=cmax(v). compute maxprobe=1. end if. end if. compute quantc(1,3) = 1. do if (quantile = 1). compute quantd(1,3) = 1. compute quantc(1,3) = 0. compute tmp = v. compute tmp(GRADE(v)) = v. compute matv = {tmp(trunc(n*.10),1); tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (vdich = 1). compute matv = {cmin(v); cmax(v)}. compute wvdich=1. compute cmaxv=cmax(v). compute cminv=cmin(v). end if. do if (!vmodval <> 999). compute matv = !vmodval. compute quantd(1,3) = 0. compute quantc(1,3) = 0. end if. compute modmatv(1,3)=nrow(matv). compute modmat((1:nrow(matv)), 3) = matv. compute modvnm(1,3)=vname. compute modmatp(1,3) = 1. end if. end if. do if (qerr = 0 and qlist = 1). do if (vnames(:,i)=qname). compute qerr = 0. compute qmatch = 1. compute q = dat(:,i). do if (center = 1). compute meanvec = make(n,1,csum(q)/n). compute q = q-meanvec. compute centvar = {centvar, qname}. end if. compute nvarch(1,i)=1. compute nmods = nmods + 1. compute qmean = csum(q)/n. compute tmp = q-(cons*qmean). compute qsd = sqrt((1/(n-1))*(t(tmp)*tmp)). compute qdich = 1. loop jj = 1 to n. do if ((q(jj,1) <> cmin(q)) and (q(jj,1) <> cmax(q))). compute qdich = 0. break. end if. end loop. do if (qdich = 0). compute matq = {qmean-qsd; qmean; qmean+qsd}. do if (quantile = 0). do if (matq(1,1) < cmin(q)). compute matq(1,1)=cmin(q). compute minprobe=1. end if. do if (matq(3,1) > cmax(q)). compute matq(3,1)=cmax(q). compute maxprobe=1. end if. end if. compute quantc(1,4) = 1. do if (quantile = 1). compute quantd(1,4) = 1. compute quantc(1,4) = 0. compute tmp = q. compute tmp(GRADE(q)) = q. compute matq = {tmp(trunc(n*.10),1); tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (qdich = 1). compute matq = {cmin(q); cmax(q)}. end if. do if (!qmodval <> 999). compute matq = !qmodval. compute quantd(1,4) = 0. compute quantc(1,4) = 0. end if. compute modmatv(1,4)=nrow(matq). compute modmat((1:nrow(matq)), 4) = matq. compute modvnm(1,4)=qname. compute modmatp(1,4) = 1. end if. end if. do if (vnames(:,i)=clname). compute cld = dat(:,i). compute cvname = vnames(:,i). compute nvarch(1,i)=1. compute clsmtch = 1. end if. loop j = 1 to ncol(mnames). do if (vnames(:,i)=mnames(1,j)). compute mmatch = mmatch + 1. compute m(:,j)=dat(:,i). do if (center = 1 and nvarch(1,i) = 0 and mlist > 0). compute meanvec = make(n,1,csum(m(:,j))/n). compute m(:,j) = m(:,j)-meanvec. compute centvar = {centvar, mnames(1,j)}. end if. compute nvarch(1,i)=1. compute dichm = 1. loop jj = 1 to n. do if ((m(jj,j) <> cmin(m(:,j))) and (m(jj,j) <> cmax(m(:,j)))). compute dichm = 0. break. end if. end loop. do if (dichm = 1 and model > 3 and mcheck = 0). compute errs= errs+1. compute runerrs(errs,1) = 1. compute mcheck = 1. end if. do if ((model <= 3) and (ncol(mnames)=1)). compute nmods = nmods + 1. compute mmean = csum(m(:,j))/n. compute tmp = m(:,j)-(cons*mmean). compute msd = sqrt((1/(n-1))*(t(tmp)*tmp)). compute mdich = 1. loop jj = 1 to n. do if ((m(jj,j) <> cmin(m(:,j))) and (m(jj,j) <> cmax(m(:,j)))). compute mdich = 0. break. end if. end loop. do if (model = 1). compute jndich=mdich. compute jnmin=cmin(m(:,j)). compute jnmax=cmax(m(:,j)). end if. do if (mdich = 0). compute matm = {mmean-msd; mmean; mmean+msd}. do if (quantile = 0). do if (matm(1,1) < cmin(m(:,j))). compute matm(1,1)=cmin(m(:,j)). compute minprobe=1. end if. do if (matm(3,1) > cmax(m(:,j))). compute matm(3,1)=cmax(m(:,j)). compute maxprobe=1. end if. end if. compute quantc(1,5) = 1. do if (quantile = 1). compute quantd(1,5) = 1. compute quantc(1,5) = 0. compute tmp = m(:,j). compute tmp(GRADE(m(:,j))) = m(:,j). compute matm = {tmp(trunc(n*.10),1); tmp(trunc(n*.25),1); tmp(trunc(n*.50),1); tmp(trunc(n*0.75),1); tmp(trunc(n*.90),1)}. end if. end if. do if (mdich = 1). compute matm = {cmin(m); cmax(m)}. end if. do if (!mmodval <> 999). compute matm = !mmodval. compute quantd(1,5) = 0. compute quantc(1,5) = 0. end if. compute modmatv(1,5)=nrow(matm). compute modmat((1:nrow(matm)), 5) = matm. compute modvnm(1,5)=mnames(1,j). compute modmatp(1,5) = 1. end if. end if. end loop. end loop. do if (minprobe=1). compute note(notes,1) = 14. compute notes = notes + 1. end if. do if (maxprobe=1). compute note(notes,1) = 15. compute notes = notes + 1. end if. do if (clname <> "xxx" and clsmtch = 0). compute errs = errs+1. compute runerrs(errs,1) = 23. end if. do if (clname <> "xxx"). do if ((clname = zname) or (clname = vname) or (clname = wname) or (clname = xname) or (clname yname) or (clname = qname)). compute errs = errs+1. compute runerrs(errs,1) = 24. end if. end if. do if (wlist = 1 and werr = 0 and wmatch = 0). compute werr = 3. compute errs = errs+1. compute runerrs(errs,1) = 4. end if. do if (zlist = 1 and zerr = 0 and zmatch = 0). compute zerr = 3. compute errs = errs+1. compute runerrs(errs,1) = 5. end if. do if (qlist = 1 and qerr = 0 and qmatch = 0). compute qerr = 3. compute errs = errs+1. compute runerrs(errs,1) = 6. end if. do if (vlist = 1 and verr = 0 and vmatch = 0). compute verr = 3. compute errs = errs+1. compute runerrs(errs,1) = 7. end if. do if (yerr = 1). compute errs = errs+1. compute runerrs(errs,1) = 16. end if. do if (model = 6 and nmeds < 2). compute errs = errs+1. compute runerrs(errs,1) = 18. end if. do if (mmatch < ncol(mnames)). compute errs=errs+1. compute runerrs(errs,1) = 25. end if. end if. do if (clname <> "xxx"). compute cld = design(cld). compute cluster = ncol(cld). compute cld = cld(:,2:ncol(cld)). compute clsdmy = ncol(cld). do if (clsdmy > 19). compute errs = errs+1. compute runerrs(errs,1) = 26. end if. end if. do if (errs = 0). do if (rsum(quantd) > 0). compute note(notes,1) = 4. compute notes = notes+1. end if. do if (rsum(quantc) > 0). compute note(notes,1) = 5. compute notes = notes+1. end if. compute dichy = 1. loop jj = 1 to n. do if ((y(jj,1) <> cmin(y)) and (y(jj,1) <> cmax(y))). compute dichy = 0. break. end if. end loop. do if (dichy = 1). compute jncrit=xp2*xp2. end if. compute ncovs = ncol(dat)-rsum(nvarch). do if (ncovs > 0). compute c = make(n,ncovs,0). compute cnames = {"x"}. compute j = 1. loop i = 1 to ncol(vnames). do if (nvarch(1,i)) = 0. compute c(:,j) = dat(:,i). compute nvarch(1,i)=1. compute j=j+1. compute cnames = {cnames, vnames(:,i)}. end if. end loop. compute cnames = cnames(1,2:ncol(cnames)). end if. compute names = {yname, xname, mnames, wname, zname, vname, qname}. do if (ncovs > 0). compute names = {names, cnames}. end if. do if (dichy = 1 and effsize = 1). compute note(notes,1) = 2. compute notes = notes+1. end if. do if (model > 3 and model < 6). compute indeff=make(nmeds,1,0). compute indboot=make(boot+1,nmeds,999). do if (effsize = 1 and dichy = 0 and ncovs = 0). compute rmeff=make(boot+1,nmeds+1,999). compute abpseff=make(boot+1,nmeds+1,999). compute abcseff=make(boot+1,nmeds+1,999). compute pmeff=make(boot+1,nmeds+1,999). compute r245 = make(boot+1,1,999). compute kappa2 = make(boot+1,1,999). end if. end if. do if (model = 6 and effsize = 1 and dichy = 0 and ncovs=0). compute rmeff=make(boot+1,ncol(indboot),999). compute abpseff=make(boot+1,ncol(indboot),999). compute abcseff=make(boot+1,ncol(indboot),999). compute pmeff=make(boot+1,ncol(indboot),999). end if. do if (nmods > 0). compute tmp = 1. loop i = 1 to 5. do if (modmatp(1,i) = 1). compute modmat(:,tmp) = modmat(:,i). compute modvnm(1,tmp) = modvnm(1,i). compute modmatv(1,tmp) = modmatv(1,i). compute tmp=tmp+1. end if. end loop. compute modmat=modmat(:,1:nmods). compute modvnm=modvnm(:,1:nmods). compute modmatv=modmatv(:,1:nmods). loop i = 1 to (ncol(modmatv)-1). compute tmp = 1. loop j = (i+1) to ncol(modmatv). compute tmp = tmp*modmatv(1,j). end loop. compute modprod(1,i)=tmp. end loop. compute modvals = make((modmatv(1,1)*modprod(1,1)), nmods,0). loop i = 1 to nmods. compute strt = 1. compute fnsh=0. loop if (fnsh < nrow(modvals)). loop j = 1 to modmatv(1,i). compute tmp=make(modprod(1,i),1,modmat(j,i)). compute fnsh = fnsh+nrow(tmp). compute modvals(strt:fnsh, i) = tmp. compute strt = fnsh+1. end loop. end loop. end loop. do if (model = 74). compute modvals=matx. compute modvnm=xname. end if. compute vmat = make(8,nrow(modvals),0). compute vmat(1,1:nrow(modvals)) = make(1,nrow(modvals),1). compute vmat(5,1:nrow(modvals)) = make(1,nrow(modvals),1). compute indeff=make(nrow(modvals),1,0). do if (model <> 5). compute indboot = make(((boot+1)*nmeds), nrow(modvals), -99999999). compute indbootp = make(boot+1,nmeds, -99999999). end if. end if. do if (nmods> 0). loop i = 1 to ncol(modvals). do if (modvnm(1,i)=wname). compute wcol = i. end if. do if (modvnm(1,i)=zname). compute zcol = i. end if. do if (modvnm(1,i)=vname). compute vcol = i. end if. do if (modvnm(1,i)=qname). compute qcol = i. end if. end loop. end if. do if (dichy = 1). compute omx = cmax(y). compute omn = cmin(y). compute y = (y = omx). compute rcd = {omn, 0; omx, 1}. end if. compute data = {cons,y,m,x}. compute datamed = data. compute datayed = data. compute datanm = {"constant"; yname; t(mnames); xname}. compute datanmm = {"constant"; yname; t(mnames); xname}. compute datanmy = {"constant"; yname; t(mnames); xname}. compute yintkey = {" ", " ", " ", " ", " ", " "}. do if (model < 4 and errs = 0). compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", mnames, " ", " "}. compute datayed = {datayed, x&*m}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. loop i = 1 to nrow(modvals). compute vmat(1,i) = 1. compute vmat(2,i) = modvals(i,1). end loop. compute mmat = make(16,nmeds,1). end if. do if (model = 2 or model = 3). compute int1 = x&*w. compute datayed = {datayed, w, int1}. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, " ", " "}. compute datanmy = {datanmy; wname; yintemp(1,intcnt)}. compute intcnt = intcnt+1. loop i = 1 to nrow(modvals). compute vmat(2,i) = modvals(i,2). compute vmat(3,i) = modvals(i,1). compute vmat(4,i) = modvals(i,1)*modvals(i,2). end loop. end if. do if (model = 3). compute yintkey = {yintkey; yintemp(1,intcnt), mnames, " X", wname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. compute int1 = w&*m. compute int2 = x&*w&*m. compute datayed = {datayed, int1, int2}. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", mnames, " X", wname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (model = 4 or model = 5). compute vmat = make(8,1,1). end if. compute yintkey2 = yintkey. do if (wm = 1). compute int1 = x&*w. compute datamed = {datamed, w,int1}. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, " ", " "}. compute datanmm = {datanmm; wname; yintemp(1,intcnt)}. compute intcnt = intcnt+1. loop i = 1 to nrow(modvals). compute vmat(2,i) = modvals(i,wcol). end loop. do if (zm = 1). compute int1 = x&*z. compute datamed = {datamed, z, int1}. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", zname, " ", " "}. compute datanmm = {datanmm; zname; yintemp(1,intcnt)}. compute intcnt = intcnt+1. loop i = 1 to nrow(modvals). compute vmat(3,i) = modvals(i,zcol). end loop. end if. do if (wzm = 1). compute yintkey = {yintkey; yintemp(1,intcnt), wname, " X", zname, " ", " "}. compute datanmm = {datanmm; yintemp(1,intcnt)}. compute intcnt = intcnt+1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, " X", zname }. compute datanmm = {datanmm; yintemp(1,intcnt)}. compute intcnt = intcnt+1. compute int1 = w&*z. compute int2 = x&*w&*z. compute datamed = {datamed, int1, int2}. loop i = 1 to nrow(modvals). compute vmat(4,i) = modvals(i,wcol)*modvals(i,zcol). end loop. end if. end if. compute mdatacol=ncol(datamed). compute mintkey = yintkey. compute yintkey = {" ", " ", " ", " ", " ", " "}. compute medints = intcnt-1. do if (vy = 1 or xmy = 1). compute mp = 1. do if (xmy = 1). loop i = 1 to nrow(modvals). compute vmat(6,i) = modvals(i,1). end loop. end if. do if (vy = 1). compute datayed = {datayed, v}. compute datanmy = {datanmy; vname}. compute mmods = 1. loop i = 1 to nrow(modvals). compute vmat(6,i) = modvals(i,vcol). end loop. do if (qy = 1). compute mp = 2. compute datayed = {datayed,q}. compute datanmy = {datanmy; qname}. compute mmods = 2. loop i = 1 to nrow(modvals). compute vmat(7,i) = modvals(i,qcol). end loop. end if. do if (vqy = 1). compute mp = 3. compute datayed = {datayed, v&*q}. compute mmods = 3. loop i = 1 to nrow(modvals). compute vmat(8,i) = modvals(i,vcol)*modvals(i,qcol). end loop. end if. end if. compute mints = make(n,(nmeds*mp),0). loop i = 0 to (nmeds-1). do if (i = 0 and vqy = 1). compute yintkey = {yintkey; yintemp(1,intcnt), vname, " X", qname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (vy = 1). compute mints(:,((i*mp)+1))= m(:,(i+1))&*v. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", vname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (xmy = 1). compute mints(:,((i*mp)+1))= m(:,(i+1))&*x. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", xname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (qy = 1). compute mints(:,((i*mp)+2))=m(:,(i+1))&*q. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", qname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. do if (vqy = 1). compute mints(:,((i*mp)+3))=m(:,(i+1))&*v&*q. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", vname, " X", qname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. end if. end loop. compute datayed = {datayed, mints}. end if. compute mp = 1. do if (wvmy = 1). compute mp = 2. loop i = 1 to nrow(modvals). compute vmat(8,i) = modvals(i,wcol)*modvals(i,vcol). end loop. end if. compute mints2 = make(n,(nmeds*mp),0). do if (wmy = 1). loop i = 1 to nrow(modvals). compute vmat(7,i) = modvals(i,wcol). end loop. do if (wy = 0 and model > 3). compute datayed = {datayed, w}. compute datanmy = {datanmy; wname}. end if. loop i = 0 to (nmeds-1). do if (i = 0 and wvmy = 1). compute datayed = {datayed,w&*v}. compute yintkey = {yintkey; yintemp(1,intcnt), wname, " X", vname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. compute mints2(:,((i*mp)+1))= m(:,(i+1))&*w. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", wname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. do if (wvmy = 1). compute mints2(:,((i*mp)+2))= m(:,(i+1))&*w&*v. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", wname, " X", vname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. end loop. compute datayed = {datayed, mints2}. end if. compute mp = 1. do if (zmy = 1). loop i = 1 to nrow(modvals). compute vmat(6,i) = modvals(i,zcol). end loop. do if (wzmy = 1). compute mp = 2. loop i = 1 to nrow(modvals). compute vmat(8,i) = modvals(i,zcol)&*modvals(i,wcol). end loop. end if. end if. do if (zmy = 1). compute mints3 = make(n,(nmeds*mp),0). do if (zy = 0). compute datayed = {datayed, z}. compute datanmy = {datanmy; zname}. end if. loop i = 0 to (nmeds-1). do if (i = 0 and wzmy = 1 and wzy = 0). compute datayed = {datayed,w&*z}. compute yintkey = {yintkey; yintemp(1,intcnt), wname, " X", zname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. compute mints3(:,((i*mp)+1))= m(:,(i+1))&*z. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", zname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. do if (wzmy = 1). compute mints3(:,((i*mp)+2))= m(:,(i+1))&*w&*z. compute yintkey = {yintkey; yintemp(1,intcnt), mnames(1,(i+1)), " X", wname, " X", zname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. end loop. compute datayed = {datayed, mints3}. end if. compute decoc = 1. compute modmat = make(5,5,999). compute modmatv = make(1,5,1). compute modmatp = make(1,5,0). compute modprod = modmatv. do if (wy = 1 and model > 3). compute datayed = {datayed, w, x&*w}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute modmatv(1,1)=nrow(matw). compute modmat((1:nrow(matw)), 1) = matw. compute modvnm2(1,1)=wname. compute modmatp(1,1) = 1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, " ", " "}. compute datanmy = {datanmy; wname; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (zy = 1). compute datayed = {datayed,z,x&*z}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute modmatv(1,2)=nrow(matz). compute modmat((1:nrow(matz)), 2) = matz. compute modvnm2(1,2)=zname. compute modmatp(1,2) = 1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", zname, " ", " "}. compute datanmy = {datanmy; zname; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (wzy = 1). compute datayed = {datayed,w&*z,x&*w&*z}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute yintkey = {yintkey; yintemp(1,intcnt), wname, " X", zname, " ", " "}. compute datanmy = {datanmy;yintemp(1,intcnt)}. compute intcnt = intcnt+1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, " X", zname }. compute datanmy = {datanmy;yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. do if (vxy = 1). compute datayed = {datayed, x&*v}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute modmatv(1,3)=nrow(matv). compute modmat((1:nrow(matv)), 3) = matv. compute modvnm2(1,3)=vname. compute modmatp(1,3) = 1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", vname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. do if (qxy = 1). compute datayed = {datayed, x&*q}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute modmatv(1,4)=nrow(matq). compute modmat((1:nrow(matq)), 4) = matq. compute modvnm2(1,4)=qname. compute modmatp(1,4) = 1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", qname, " ", " "}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. do if (vqxy = 1). compute datayed = {datayed, x&*v&*q}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", vname, "X", qname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. end if. end if. do if (wvxy = 1). compute datayed = {datayed, x&*w&*v}. compute decoc = decoc+1. compute deco(decoc,1) = ncol(datayed)-1. compute yintkey = {yintkey; yintemp(1,intcnt), xname, " X", wname, "X", vname}. compute datanmy = {datanmy; yintemp(1,intcnt)}. compute intcnt = intcnt+1. end if. compute modvalsd = 0. compute ttt = rsum(modmatp). do if (rsum(modmatp) > 0). compute tmp = 1. loop i = 1 to 5. do if (modmatp(1,i) = 1). compute modmat(:,tmp) = modmat(:,i). compute modvnm2(1,tmp) = modvnm2(1,i). compute modmatv(1,tmp) = modmatv(1,i). compute tmp=tmp+1. end if. end loop. compute modmat=modmat(:,1:ttt). compute modvnm2=modvnm2(:,1:ttt). compute modmatv=modmatv(:,1:ttt). loop i = 1 to (ncol(modmatv)-1). compute tmp = 1. loop j = (i+1) to ncol(modmatv). compute tmp = tmp*modmatv(1,j). end loop. compute modprod(1,i)=tmp. end loop. compute modvalsd = make((modmatv(1,1)*modprod(1,1)), ttt,0). loop i = 1 to ttt. compute strt = 1. compute fnsh=0. loop if (fnsh < nrow(modvalsd)). loop j = 1 to modmatv(1,i). compute tmp=make(modprod(1,i),1,modmat(j,i)). compute fnsh = fnsh+nrow(tmp). compute modvalsd(strt:fnsh, i) = tmp. compute strt = fnsh+1. end loop. end loop. end loop. end if. do if (ttt > 0). loop i = 1 to ncol(modvalsd). do if (modvnm2(1,i)=wname). compute wcol = i. end if. do if (modvnm2(1,i)=zname). compute zcol = i. end if. do if (modvnm2(1,i)=vname). compute vcol = i. end if. do if (modvnm2(1,i)=qname). compute qcol = i. end if. end loop. compute directv = make(nrow(modvalsd),1,1). do if (wy = 1). compute directv ={directv, modvalsd(:,wcol)}. end if. do if (zy = 1). compute directv ={directv, modvalsd(:,zcol)}. end if. do if (wzy = 1). compute directv ={directv, (modvalsd(:,wcol)&*modvalsd(:,zcol))}. end if. do if (vxy = 1). compute directv ={directv, modvalsd(:,vcol)}. end if. do if (qxy = 1). compute directv ={directv, modvalsd(:,qcol)}. end if. do if (vqxy = 1). compute directv ={directv, (modvalsd(:,vcol)&*modvalsd(:,qcol))}. end if. do if (wvxy = 1). compute directv ={directv, (modvalsd(:,vcol)&*modvalsd(:,wcol))}. end if. end if. compute ydatacol=ncol(datayed). do if (ncovs > 0). do if (covmy <> 2). compute datamed = {datamed,c}. end if. do if (covmy <> 1). compute datayed = {datayed,c}. end if. compute covmeans = csum(c)/n. end if. do if (cluster > 0). compute datamed = {datamed,cld}. compute datayed = {datayed, cld}. compute cldmeans = csum(cld)/n. end if. compute mst = 3. compute mnd = mst+nmeds-1. compute ydatacol=ncol(datayed). compute mdatacol=ncol(datamed). do if (ncovs > 0). compute datanmy = {datanmy; t(cnames)}. do if (model > 3). compute datanmm = {datanmm; t(cnames)}. end if. end if. compute datanmy = {"constant"; datanmy(3:nrow(datanmy),1)}. do if (model > 3). compute datanmm = {"constant"; datanmm(3:nrow(datanmm),1)}. end if. compute amm = make(2,1,0). compute abmm = make(2,1,0). compute mnv = csum(datayed(:,2)/n). compute mnv = make(n,1,mnv). compute ssty = csum((datayed(:,2)-mnv)&**2). compute sigma = (n*sscp(datayed))-(t(csum(datayed))*(csum(datayed))). compute sigma = sigma/(n*(n-1)). compute stddevy = sqrt(sigma(2,2)). compute stddevx = sqrt(sigma((3+nmeds),(3+nmeds))). compute r2xy = (sigma(2,(3+nmeds))/(stddevy*stddevx))&**2. compute r2my = (sigma(2,3)/(stddevy*sqrt(sigma(3,3))))&**2. compute ctot = sigma(2,(3+nmeds))/sigma((3+nmeds),(3+nmeds)). do if (model = 4 and nmeds = 1 and cluster = 0 and ncovs = 0). compute kappaa = sigma(2,3)*sigma(2,4). compute kappab = sqrt((sigma(3,3)*sigma(2,2))-(sigma(2,3)*sigma(2,3))). compute kappac = sqrt((sigma(4,4)*sigma(2,2))-(sigma(2,4)*sigma(2,4))). compute kappad = sigma(4,4)*sigma(2,2). compute kappae = sqrt((sigma(4,4)*sigma(3,3))-(sigma(3,4)*sigma(3,4))). compute amm(1,1) = (kappaa+(kappab*kappac))/kappad. compute amm(2,1) = (kappaa-(kappab*kappac))/kappad. do if (sigma(3,4) < 0). compute amma =cmin(amm). end if. do if (sigma(3,4) > 0). compute amma = cmax(amm). end if. compute abmm(1,1)=-amma*(kappac/kappae). compute abmm(2,1)=amma*(kappac/kappae). end if. compute datatm = datamed. compute dataty = datayed. compute mdlnms2 = {!quote(!model); yname; xname}. compute mdlnms = {"Model ="; " Y ="; " X =" }. loop i = 1 to ncol(mnames). compute mdlnms2 = {mdlnms2; mnames(1,i)}. do if (i = 1 and ncol(mnames) = 1). compute mdlnms = {mdlnms; " M ="}. else. compute mdlnms = {mdlnms; mlab(i,1)}. end if. end loop. do if (wname <> "xxx"). compute mdlnms2 = {mdlnms2; wname}. compute mdlnms = {mdlnms; " W = "}. end if. do if (zname <> "xxx"). compute mdlnms2 = {mdlnms2; zname}. compute mdlnms = {mdlnms; " Z = "}. end if. do if (vname <> "xxx"). compute mdlnms2 = {mdlnms2; vname}. compute mdlnms = {mdlnms; " V = "}. end if. do if (qname <> "xxx"). compute mdlnms2 = {mdlnms2; qname}. compute mdlnms = {mdlnms; " Q = "}. end if. do if (jn = 1 and model = 1 and jndich = 1). compute note(notes,1) = 8. compute notes = notes + 1. end if. do if (jn = 1 and model = 3 and jndich = 1). compute note(notes,1) = 8. compute notes = notes + 1. end if. do if (effsize = 1 and ncovs <> 0). compute note(notes,1) = 10. compute notes = notes + 1. end if. print/title = "***************** PROCESS Procedure for SPSS Release 2.10 ****************". print/title = " Written by Andrew F. Hayes, Ph.D. www.afhayes.com". print/title = " Documentation available in Hayes (2013). www.guilford.com/p/hayes3"/space=0. print mdlnms2/title = "**************************************************************************"+ ""/rnames = mdlnms/format = a8. do if (ncovs > 0). print cnames/title = "Statistical Controls:"/rlabels = "CONTROL="/format a8. end if. print n/title = "Sample size"/format F10.0. do if (cluster > 0). print cluster/rnames = cvname/title = "Clustering Variable and Number of Clusters". end if. loop bt = 1 to (boot+1). do if (bt > 1). loop. compute v=trunc(uniform(n,1)*n)+1. compute datayed = dataty(v,:). compute detcheck=det(t(datayed)*datayed). compute rk=(detcheck <> 0). do if (model > 3). compute datamed = datatm(v,:). compute detcheck=det(t(datamed)*datamed). do if (rk =1). compute rk=(detcheck <> 0). end if. end if. compute sigma = (n*sscp(datayed))-(t(csum(datayed))*(csum(datayed))). compute sigma = sigma/(n*(n-1)). compute temp=diag(sigma). /* do if (rk = 1) */. /* compute rk = (csum(temp(2:nrow(temp)) = 0) = 0) */. /* end if */. compute bad = bad+(1-rk). compute false = 1. end loop if (rk = 1). /* compute sigma = (t(datayed)*(ident(n)-(1/n)*cons*t(cons))*datayed)*(1/(n-1)) */. compute stddevy = sqrt(sigma(2,2)). compute stddevx = sqrt(sigma((3+nmeds),(3+nmeds))). compute ctot = sigma(2,(3+nmeds))/sigma((3+nmeds),(3+nmeds)). do if (model = 4 and nmeds = 1 and ncovs = 0 and cluster = 0). compute r2xy = (sigma(2,4)/(stddevy*stddevx))&**2. compute r2my = (sigma(2,3)/(stddevy*sqrt(sigma(3,3))))&**2. compute sstot = sigma(2,2)*(n-1). compute kappaa = sigma(2,3)*sigma(2,4). compute kappab = sqrt((sigma(3,3)*sigma(2,2))-(sigma(2,3)*sigma(2,3))). compute kappac = sqrt((sigma(4,4)*sigma(2,2))-(sigma(2,4)*sigma(2,4))). compute kappad = sigma(4,4)*sigma(2,2). compute kappae = sqrt((sigma(4,4)*sigma(3,3))-(sigma(3,4)*sigma(3,4))). compute amm(1,1) = (kappaa+(kappab*kappac))/kappad. compute amm(2,1) = (kappaa-(kappab*kappac))/kappad. do if (sigma(3,4) < 0). compute amma =cmin(amm). end if. do if (sigma(3,4) > 0). compute amma = cmax(amm). end if. compute abmm(1,1)=-amma*(kappac/kappae). compute abmm(2,1)=amma*(kappac/kappae). end if. end if. /* estimate model of mediator(s) */. do if (model > 3). loop im = 1 to nmeds. compute xm={cons, datamed(:,(mnd+1):mdatacol)}. compute xmnm = {"constant"; datanmm((2+nmeds):nrow(datanmm),1)}. compute invXtX = inv(t(xm)*xm). compute coeff =invXtX*t(xm)*datamed(:,(2+im)). do if (model = 6). do if (im = 1). compute xm={cons, datamed(:,(mnd+1):mdatacol)}. compute invXtX = inv(t(xm)*xm). compute coeff =invXtX*t(xm)*datamed(:,(2+im)). end if. do if (im > 1). compute xm={cons, datamed(:,3:(im+1)), datamed(:,(mnd+1):mdatacol)}. compute xmnm = {"constant"; datanmm(2:im,1); datanmm((mnd):nrow(datanmm),1)}. compute invXtX = inv(t(xm)*xm). compute coeff =invXtX*t(xm)*datamed(:,(2+im)). compute mmpaths((im+1),(2:im))=t(coeff(2:im,1)). end if. end if. do if (bt = 1). compute resid=datamed(:,(2+im))-xm*coeff. compute sse =cssq(resid). compute mse = sse/(n-ncol(xm)). compute mnv = csum(data(:,(2+im))/n). compute mnv = make(n,1,mnv). compute sstm = csum((data(:,(2+im))-mnv)&**2). compute k3 = nrow(coeff). do if (hc3 = 1). compute h = xm(:,1). loop i3=1 to n. compute h(i3,1)= xm(i3,:)*invXtX*t(xm(i3,:)). end loop. loop i3=1 to k3. compute xm(:,i3) = (resid(:,ncol(resid))&/(1-h))&*xm(:,i3). end loop. end if. do if (hc3 <> 1). loop i3=1 to k3. compute xm(:,i3) = sqrt(mse)&*xm(:,i3). end loop. end if. compute lmat = ident(nrow(coeff)). compute lmat = lmat(:,2:ncol(lmat)). compute hccov=invXtX*t(xm)*xm*invXtX. compute dfnum = nrow(coeff)-1. compute dfden = n-dfnum-1. compute fratio = (t(t(lmat)*coeff)*inv(t(lmat)*hccov*lmat)*((t(lmat)*coeff)))/dfnum). compute coeff = coeff(1:(nrow(coeff)-clsdmy)). compute standerr = sqrt(diag(invXtX*t(xm)*xm*invXtX)). compute standerr = standerr(1:(nrow(standerr)-clsdmy)). compute tratio = coeff&/standerr. compute p = 2*(1-tcdf(abs(tratio), (n-ncol(xm)))). compute temp=(n-ncol(xm)). compute xd = abs(xp2). compute temp = (temp* (exp((temp-(5/6))*((xd/(temp-(2/3)+(.11/temp)))*(xd/(temp-(2/3)+ (.11/temp)))))-1)). compute temp1 = coeff-sqrt(abs(temp))*standerr. compute temp2 = coeff+sqrt(abs(temp))*standerr. compute op = {coeff, standerr, tratio, p, temp1, temp2}. compute sobel(im,1) = coeff(2,1). compute sobel(im,2)=standerr(2,1). compute temp = mnames(1,im). compute r2full = 1-(sse/sstm). /* compute fratio = (dfden*r2full)/((1-r2full)*dfnum) */. compute pfr = 1-fcdf(fratio,dfnum,dfden). compute summ = {sqrt(r2full), r2full, Fratio, dfnum, dfden, pfr}. do if (detail = 1). print temp/title = "***************************************************************"+ "***********"/rlabels = "Outcome:"/format = A8. /* do if (cluster = 0) */. print summ/title = "Model Summary"/clabels "R", "R-sq", "F", "df1", "df2", "p"/format !decimals. /* end if */. do if (coeffci = 0). compute op = op(:,1:(ncol(op)-2)). end if. print op/title = "Model"/rnames = xmnm/clabels = "coeff", "se", "t", "p", "LLCI", "ULCI"/format = !decimals. do if (nmods > 0 and nrow(mintkey) > 1). print mintkey/title = "Interactions:"/format = A8. end if. end if. end if. /* now we create the matrices for indirect effects */. compute ymat(1,im) = coeff(2,1). do if (wm = 1). compute ymat(2,im) = coeff(4,1). do if (zm = 1). compute ymat(3,im) = coeff(6,1). do if (wzm = 1). compute ymat(4, im) = coeff(8,1). end if. end if. end if. do if (model = 6). compute mmpaths((im+1),1)=coeff((im+1),1). end if. end loop. end if. /* estimate model of outcome */. loop totlp = 1 to (1+(toteff*(bt = 1))). do if (toteff = 1 and totlp =2). compute xy = {cons,datayed(:,(3+nmeds):ydatacol)}. else. compute xy={cons, datayed(:,3:ydatacol)}. end if. do if (dichy = 1). compute pt2 = make(nrow(datayed(:,2)),1,(csum(datayed(:,2))/n)). compute LL3 = datayed(:,2)&*ln(pt2)+(1-datayed(:,2))&*ln(1-pt2). compute LL3 = -2*csum(LL3). compute pt1 = make(n,1,0.5). compute bt1 = make(ncol(xy),1,0). compute LL1 = 0. compute xy22=xy. loop jjj = 1 to iterate. loop ijk=1 to ncol(xy). compute xy22(:,ijk)=xy(:,ijk)&*pt1&*(1-pt1). end loop. compute coeff = bt1+inv(t(xy22)*xy)*t(xy)*(datayed(:,2)-pt1). compute pt1 = 1/(1+exp(-(xy*coeff))). compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)). do if (itprob = 0). compute LL = datayed(:,2)&*ln(pt1)+(1-datayed(:,2))&*ln(1-pt1). compute LL2 = -2*csum(ll). end if. do if (abs(LL1-LL2) < converge). break. end if. compute bt1 = coeff. compute LL1 = LL2. end loop. do if (jjj >= iterate and iterr = 0). compute errs = errs+1. compute runerrs(errs,1) = 22. computer iterr = 1. end if. loop ijk=1 to ncol(xy). compute xy22(:,ijk)=xy(:,ijk)&*pt1&*(1-pt1). end loop. compute covmat = inv(t(xy22)*xy). release xy22. end if. do if (dichy = 0). compute invXtX = inv(t(xy)*xy). compute coeff =invXtX*t(xy)*datayed(:,2). do if (nmeds = 1 and ncovs = 0 and cluster = 0 and model = 4 and bt > 1). compute resid=datayed(:,2)-xy*coeff. compute sse = cssq(resid). compute r2full = 1-(sse/sstot). end if. do if (bt =1). compute resid=data(:,2)-xy*coeff. compute k3 = nrow(coeff). compute sse = cssq(resid). compute mse = sse/(n-ncol(xy)). do if (hc3 = 1). compute h = xy(:,1). loop i3=1 to n. compute h(i3,1)= xy(i3,:)*invXtX*t(xy(i3,:)). end loop. loop i3=1 to k3. compute xy(:,i3) = (resid(:,ncol(resid))&/(1-h))&*xy(:,i3). end loop. end if. do if (hc3 <> 1). loop i3=1 to k3. compute xy(:,i3) = sqrt(mse)&*xy(:,i3). end loop. end if. compute covmat = (invXtX*t(xy)*xy*invXtX). end if. end if. do if (bt = 1). do if (model = 2). compute xy2={cons, datayed(:,3:ydatacol)}. compute temp = ncol(xy2). do if (temp > 6). compute xy3=xy2(:,7:temp)}. end if. compute xy2={xy2(:,1:3), xy2(:,5)}. do if (temp > 6). compute xy2={xy2, xy3}. release xy3. end if. compute invXtX = inv(t(xy2)*xy2). compute coeff2 =invXtX*t(xy2)*datayed(:,2). compute ssem2=cssq(datayed(:,2)-xy2*coeff2). release xy2. end if. compute standerr = sqrt(diag(covmat)). compute standerr=standerr(1:(nrow(standerr)-clsdmy),1). compute coeffplt = coeff. compute lmat = ident(nrow(coeff)). compute lmat = lmat(:,2:ncol(lmat)). compute dfnum = nrow(coeff)-1. compute dfden = n-dfnum-1. compute fratio = (t(t(lmat)*coeff)*inv(t(lmat)*covmat*lmat)*((t(lmat)*coeff)))/dfnum). compute coeff=coeff(1:(nrow(coeff)-clsdmy),1). compute bbbb=coeff(2,1). do if totlp = 1. compute deco(1,1)=2+nmeds. compute deco = deco(1:decoc,1). compute covdirt = make((nrow(covmat)-clsdmy),(ncol(covmat)-clsdmy),0). compute covdirt = covmat(deco,:). compute covdir = make(nrow(covdirt),ncol(covdirt),0). compute covdir = covdirt(:,t(deco)). compute deco=coeff(deco,1). do if (ttt > 0). compute sedir = sqrt(diag(directv*covdir*t(directv))). compute directv = directv*deco. end if. compute sobel(:,3)=coeff(2:(1+nmeds),1). compute sobel(:,4) = standerr(2:(1+nmeds),1). compute sobel2 = sobel&*sobel. do if (varorder <> 2). compute sobel(:,2) = sqrt(sobel2(:,1)&*sobel2(:,4)+sobel2(:,3)&*sobel2(:,2)). end if. do if (varorder = 2). compute sobel(:,2) = sqrt(sobel2(:,1)&*sobel2(:,4)+sobel2(:,3)&*sobel2(:,2)+sobel2(:, 2)&*sobel2(:,4)). end if. compute sobel(:,1) = sobel(:,1)&*sobel(:,3). compute sobel(:,3) = sobel(:,1)&/sobel(:,2). compute sobel(:,4) = 2*(1-cdfnorm(abs(sobel(:,3)))). end if. do if (dichy = 0). compute tratio = coeff&/standerr. compute p = 2*(1-tcdf(abs(tratio), (n-ncol(xy)))). compute cnms = {"coeff", "se", "t", "p", "LLCI", "ULCI"}. compute op = {coeff, standerr, tratio, p}. end if. do if (dichy = 1). compute tratio = (coeff&/standerr). compute p = 2*(1-cdfnorm(abs(tratio))). compute wald = tratio&*tratio. compute cnms = {"coeff", "se", "Z", "p", "LLCI", "ULCI"}. compute temp=coeff-abs(xp2)*standerr. compute op = {coeff, standerr, tratio, p, temp}. compute temp=coeff+abs(xp2)*standerr. compute op = {op, temp}. end if. do if (detail = 1). do if (totlp = 2). print yname/title = "************************** TOTAL EFFECT MODEL "+ "****************************"/rlabels = "Outcome:"/format = A8. end if. do if (totlp <> 2). print yname/title = "**************************************************************"+ "************"/rlabels = "Outcome:"/format = A8. end if. end if. do if (dichy = 1 and bt = 1 and totlp = 1). compute nmsd = {yname, "Analysis"}. print rcd/title = "Coding of binary DV for analysis:"/cnames = nmsd/format = F9.2. end if. do if (dichy = 0). compute r2full = 1-(sse/ssty). /* compute fratio = (dfden*r2full)/((1-r2full)*dfnum) */. compute pfr = 1-fcdf(fratio,dfnum,dfden). compute jndf=dfden. compute xd = abs(xp2). compute jncrit = (dfden* (exp((dfden-(5/6))*((xd/(dfden-(2/3)+(.11/dfden)))* (xd/(dfden-(2/3)+(.11/dfden)))))-1)). compute summ = {sqrt(r2full), r2full, fratio, dfnum, dfden, pfr}. compute temp1=coeff-sqrt(jncrit)*standerr. compute temp2=coeff+sqrt(jncrit)*standerr. compute op = {coeff, standerr, tratio, p, temp1, temp2}. do if (detail = 1). /* do if (cluster = 0) */. print summ/title = "Model Summary"/clabels = "R", "R-sq", "F", "df1", "df2", "p"/format = !decimals. /* end if */. end if. end if. do if (dichy = 1). compute LLdiff = LL3-LL2. compute mcF = LLdiff/LL3. compute cox = 1-exp(-LLdiff/n). compute nagel = cox/(1-exp(-(LL3)/n)). compute pf = {LL2, LLdiff, mcF, cox, nagel, n}. do if (detail = 1). print pf/title = "Logistic Regression Summary"/clabels = "-2LL" "Model LL" "McFadden" "CoxSnell" "Nagelkrk" "n"/format = !decimals. end if. end if. do if (totlp = 2). compute datanmy={"constant"; datanmy((nmeds+2):nrow(datanmy),1)}. end if. do if (detail = 1). do if (coeffci = 0). compute op = op(:,1:(ncol(op)-2)). end if. print op/title = "Model"/rnames = datanmy/cnames = cnms/format = !decimals. end if. do if (ttt = 0 and totlp = 1). compute deco = op((nmeds+2),:). end if. do if (ttt = 0 and totlp = 2). compute decotot = op(2,:). end if. do if (nmods > 0 and model > 4 and detail = 1 and nrow(yintkey) > 1)). print yintkey/title = "Interactions:"/format = A8. end if. do if (nmods > 0 and model < 4 and detail = 1). print yintkey2/title = "Interactions:"/format = A8. do if ((model = 1 or model = 2) and dichy = 0 and hc3 = 0). compute temp={((op(4,3)**2)*(1-r2full))/dfden, op(4,3)**2, 1, dfden, op(4,4)}. compute rnms=yintkey2(2,1). do if (model = 2). compute temp={temp;((op(6,3)**2)*(1-r2full))/dfden, op(6,3)**2, 1, dfden, op(6,4)}. compute frat2=(dfden*(r2full-(1-(ssem2/ssty))))/(2*(1-r2full)). compute temp={temp;(r2full-(1-(ssem2/ssty))),frat2,2,dfden,1-fcdf(frat2,2,dfden)}. compute rnms={rnms; yintkey2(3,1);"Both"}. end if. print temp/title = "R-square increase due to interaction(s):"/rnames=rnms/clabels "R2-chng", "F", "df1", "df2", "p"/format = !decimals. end if. do if (model = 3 and dichy = 0 and hc3 = 0). compute temp={((op(8,3)**2)*(1-r2full))/dfden, op(8,3)**2, dfden, op(8,4)}. compute rnms=yintkey2(5,1). print temp/title = "R-square increase due to three-way "+ "interaction:"/rnames=rnms/clabels = "R2-chng", "F(1,df2)", "df2", "p"/format = !decimals. end if. end if. end if. do if (model = 6 and totlp = 1). compute mmpaths(nrow(mmpaths),1)=coeff(nrow(mmpaths),1). compute mmpaths(nrow(mmpaths),(2:(nmeds+1)))=t(coeff(2:(nmeds+1),1)). end if. do if (totlp = 1). loop im = 1 to nmeds. do if (model < 4). compute ymat(1,im) = coeff(3,1). compute ymat(2,im) = coeff(4,1). compute cmat(1,im) = covmat(3,3). compute cmat(2,im) = covmat(4,4). compute cmat(5,im) = covmat(3,4). compute jnb1=coeff(3,1). compute jnb3=coeff(4,1). compute jnsb1=covmat(3,3). compute jnsb3=covmat(4,4). compute jnsb1b3=covmat(3,4). do if (model = 2 or model = 3). compute ymat(3,im) = coeff(6,1). compute cmat(3,im) = covmat(6,6). compute cmat(6,im) = covmat(3,6). compute cmat(8,im) = covmat(4,6). end if. do if (model = 3). compute ymat(4,im) = coeff(8,1). compute cmat(4,im) = covmat(8,8). compute cmat(7,im) = covmat(3,8). compute cmat(9,im) = covmat(4,8). compute cmat(10,im) = covmat(6,8). compute jnb1=coeff(4,1). compute jnb3=coeff(8,1). compute jnsb1=covmat(4,4). compute jnsb3=covmat(8,8). compute jnsb1b3=covmat(4,8). end if. end if. do if (model > 3). compute ymat(5,im) = coeff((1+im),1). end if. do if (xmy = 1). compute ymat(6,im) = coeff((2+nmeds+im),1). end if. do if (vy = 1). compute ymat(6,im) = coeff((3+nmeds+im),1). end if. do if (qy = 1 and vy = 1). compute ymat(6,im) = coeff((5+nmeds+((im-1)*2)),1). compute ymat(7,im) = coeff((6+nmeds+((im-1)*2)),1). end if. do if (vqy = 1). compute ymat(6,im) = coeff((6+nmeds+((im-1)*3)),1). compute ymat(7,im) = coeff((7+nmeds+((im-1)*3)),1). compute ymat(8,im) = coeff((8+nmeds+((im-1)*3)),1). end if. do if (wmy = 1). compute ymat(7,im) = coeff((3+nmeds+im-wy),1). end if. do if (wmy = 1 and vy = 1). compute ymat(7,im) =coeff((4+(nmeds*2)+im-wy),1). end if. do if (wmy = 1 and vy = 1 and wvmy = 1). compute ymat(7,im) = coeff((6+(nmeds*2)+((im-1)*2)-wy),1). compute ymat(8,im) = coeff((7+(nmeds*2)+((im-1)*2)-wy),1). end if. do if (wmy = 1 and zmy = 1). compute ymat(6,im) = coeff((6-(wzy*3)+(wzm-1)+(nmeds*2)+((im-1)*2)*wzm)+((im-1)*(1-wzm)) -((zy-wzy)*2),1). compute ymat(7,im) = coeff((3-zy+im+nmeds),1). do if (wzmy=1). compute ymat(8,im) = coeff((7-(wzy*3)+(nmeds*2)+((im-1)*2)),1). end if. end if. do if (nmods > 0 and model <> 5). loop indlp = 1 to nrow(modvals). compute indeff(indlp,1) = csum(ymat(1:4,im)&*vmat(1:4,indlp)). do if (model > 6). compute indeff(indlp,1) = csum(ymat(1:4,im)&*vmat(1:4,indlp))*csum(ymat(5:8,im)&*vmat(5:8,indlp)). end if. end loop. compute indboot((bt+(im-1)*(boot+1)),:)=t(indeff). do if (model = 8 or model = 7). compute indbootp(bt,im)=ymat(2,im)*ymat(5,im). do if (wdich=1). compute indbootp(bt,im)=indbootp(bt,im)*(cmaxw-cminw). end if. end if. do if (model = 14 or model = 15 or model = 74). compute indbootp(bt,im)=ymat(1,im)*ymat(6,im). do if (wvdich=1). compute indbootp(bt,im)=indbootp(bt,im)*(cmaxv-cminv). end if. end if. do if (model = 12). compute indbootp(bt,im)=ymat(4,im)*ymat(5,im). end if. do if ((model = 58 or model = 59) and wvdich=1). compute indbootp(bt,im)=(ymat(1,im)*ymat(7,im)*(cmaxw-cminw))+(ymat(2,im)*ymat(5,im)* (cmaxw-cminw))+(ymat(2,im)*ymat(7,im)*((cmaxw*cmaxw)-(cminw*cminw))). end if. end if. do if (model = 4 or model = 5). compute indboot(bt,im)=csum(ymat(1:4,im)&*vmat(1:4,1))*csum(ymat(5:8,im)&*vmat(5:8,1)). do if (effsize = 1 and dichy = 0 and ncovs = 0). do if (ctot = 0). compute ctot=.00000000000001. end if. compute pmeff(bt,(im+1))=indboot(bt,im)/ctot. compute rmeff(bt,(im+1))=indboot(bt,im)/coeff((2+nmeds),1). compute abpseff(bt,(im+1))=indboot(bt,im)/stddevy. compute abcseff(bt,(im+1))=abpseff(bt,(im+1))*stddevx. do if (nmeds = 1 and ncovs = 0 and cluster = 0 and model = 4). compute r245(bt,1) = r2my-(r2full-r2xy). /* compute temp = indboot(bt,im) */. compute abmmr = 1. do if (indboot(bt,im) < 0). compute abmmr = cmin(abmm). end if. do if (indboot(bt,im) > 0). compute abmmr = cmax(abmm). end if. compute kappa2(bt,1)=indboot(bt,im)/abmmr. compute tmp = indboot(bt,im)/abmmr. end if. end if. end if. do if (model = 6). do if (nmeds = 2). compute indboot(bt,1)=mmpaths(2,1)*mmpaths(4,2). compute indboot(bt,2)=mmpaths(2,1)*mmpaths(3,2)*mmpaths(4,3). compute indboot(bt,3)=mmpaths(3,1)*mmpaths(4,3). end if. do if (nmeds = 3). compute indboot(bt,1) = mmpaths(2,1)*mmpaths(5,2). compute indboot(bt,2) = mmpaths(2,1)*mmpaths(3,2)*mmpaths(5,3). compute indboot(bt,3) = mmpaths(2,1)*mmpaths(4,2)*mmpaths(5,4). compute indboot(bt,4) = mmpaths(2,1)*mmpaths(3,2)*mmpaths(4,3)*mmpaths(5,4). compute indboot(bt,5) = mmpaths(3,1)*mmpaths(5,3). compute indboot(bt,6) = mmpaths(3,1)*mmpaths(4,3)*mmpaths(5,4). compute indboot(bt,7) = mmpaths(4,1)*mmpaths(5,4). end if. do if (nmeds = 4). compute indboot(bt,1)=mmpaths(2,1)*mmpaths(6,2). compute indboot(bt,2)=mmpaths(2,1)*mmpaths(3,2)*mmpaths(6,3). compute indboot(bt,3)=mmpaths(2,1)*mmpaths(4,2)*mmpaths(6,4). compute indboot(bt,4)=mmpaths(2,1)*mmpaths(5,2)*mmpaths(6,5). compute indboot(bt,5)=mmpaths(2,1)*mmpaths(3,2)*mmpaths(4,3)*mmpaths(6,4). compute indboot(bt,6)=mmpaths(2,1)*mmpaths(3,2)*mmpaths(5,3)*mmpaths(6,5). compute indboot(bt,7)=mmpaths(2,1)*mmpaths(4,2)*mmpaths(5,4)*mmpaths(6,5). compute indboot(bt,8)=mmpaths(2,1)*mmpaths(3,2)*mmpaths(4,3)*mmpaths(5,4)*mmpaths(6,5) . compute indboot(bt,9)=mmpaths(3,1)*mmpaths(6,3). compute indboot(bt,10)=mmpaths(3,1)*mmpaths(4,3)*mmpaths(6,4). compute indboot(bt,11) =mmpaths(3,1)*mmpaths(5,3)*mmpaths(6,5). compute indboot(bt,12) = mmpaths(3,1)*mmpaths(4,3)*mmpaths(5,4)*mmpaths(6,5). compute indboot(bt,13) = mmpaths(4,1)*mmpaths(6,4). compute indboot(bt,14) = mmpaths(4,1)*mmpaths(5,4)*mmpaths(6,5). compute indboot(bt,15) = mmpaths(5,1)*mmpaths(6,5). end if. do if (effsize = 1 and dichy = 0 and ncovs = 0). do if (ctot = 0). compute ctot=.00000000000001. end if. compute pmeff(bt,:)=indboot(bt,:)/ctot. compute rmeff(bt,:) = indboot(bt,:)/mmpaths(nrow(mmpaths),1). compute abpseff(bt,:)=indboot(bt,:)/stddevy. compute abcseff(bt,:)=stddevx*indboot(bt,:)/stddevy. do if (nmeds = 1 and ncovs = 0 and cluster = 0 and model = 4). compute r245(bt,:) = r2my-(r2full-r2xy). end if. end if. end if. end loop. end if. end loop. /* end of outcome variable loop */. end loop. /* end of bootstrap loop */. release datayed, dat, datamed, data, y, x, datatm, dataty, mints2, cons, mnv, tmp. do if (ttt = 0 and model > 3). do if (toteff = 0). print/title = "******************** DIRECT AND INDIRECT EFFECTS *************************". else. print/title = "***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************". end if. do if (model <> 74). do if (dichy = 0). do if (toteff = 1). print decotot/title = "Total effect of X on Y"/clabels = "Effect", "SE", "t", "p", "LLCI", "ULCI"/format = !decimals. end if. print deco/title = "Direct effect of X on Y"/clabels = "Effect", "SE", "t", "p", "LLCI", "ULCI"/format = !decimals. else. do if (toteff = 1). print decotot/title = "Total effect of X on Y"/clabels = "Effect", "SE", "Z", "p", "LLCI", "ULCI"/format = !decimals. end if. print deco/title = "Direct effect of X on Y"/clabels = "Effect", "SE", "Z", "p", "LLCI", "ULCI" /format = !decimals. end if. end if. end if. do if (ttt > 0). print/title = "******************** DIRECT AND INDIRECT EFFECTS *************************". compute clbs = {modvnm2, "Effect", "SE", "t", "p", "LLCI", "ULCI"}. compute tratio = (directv&/sedir). compute p = 2*(1-tcdf(abs(tratio), (n-ncol(xy)))). compute outp = {modvalsd, directv, sedir, tratio, p}. do if (dichy = 0). compute temp1=directv-sqrt(jncrit)*sedir. compute temp2=directv+sqrt(jncrit)*sedir. compute outp = {outp, temp1, temp2}. end if. do if (dichy = 1). compute p = 2*(1-cdfnorm(abs(tratio))). compute temp = directv-abs(xp2)*sedir. compute outp = {outp, temp}. compute temp = directv+abs(xp2)*sedir. compute outp = {outp, temp}. compute clbs = {modvnm2, "Effect", "SE", "Z", "p", "LLCI", "ULCI"}. end if. do if (coeffci = 0). compute outp = outp(:,1:(ncol(outp)-2)). end if. print outp/title = "Conditional direct effect(s) of X on Y at values of the "+ "moderator(s):"/format = !decimals/cnames = clbs. end if. do if (nmods > 0 and model <> 5). do if (model < 4). print/title = "*************************************************************************". compute zmat(1,1) = 1. compute cfse = make(nrow(modvals),1,0). loop #m = 1 to nrow(modvals). do if (model = 1). compute zmat(2,1)=modvals(#m,1)**2. compute zmat(5,1)=2*modvals(#m,1). end if. do if (model = 2 or model = 3). compute zmat(2,1)=modvals(#m,2)**2. compute zmat(3,1)=modvals(#m,1)**2. compute zmat(4,1)=(modvals(#m,1)**2)*(modvals(#m,2)**2). compute zmat(5,1)=2*modvals(#m,2). compute zmat(6,1)=2*modvals(#m,1). compute zmat(7,1)=2*modvals(#m,1)*modvals(#m,2). compute zmat(8,1)=2*modvals(#m,1)*modvals(#m,2). compute zmat(9,1)=2*modvals(#m,1)*(modvals(#m,2)**2). compute zmat(10,1)=2*(modvals(#m,1)**2)*modvals(#m,2). end if. compute cfse(#m,1)=sqrt(csum(zmat&*cmat)). end loop. end if. do if (nmods > 0). compute clbs = {modvnm, "Effect"}. loop im = 1 to nmeds. compute obs = t(indboot(1+(im-1)*(boot+1),:)). compute outp = {modvals, obs}. do if (model < 4). compute tstat = obs&/cfse. do if (dichy = 0). compute pval = 2*(1-tcdf(abs(tstat), (n-ncol(xy)))). compute temp=obs-sqrt(jncrit)*cfse. compute outp = {outp, cfse, tstat, pval, temp}. compute temp=obs+sqrt(jncrit)*cfse. compute outp = {outp, temp}. compute clbs = {clbs, "se", "t", "p", "LLCI", "ULCI"}. compute jnclbs=clbs. end if. do if (dichy = 1). compute pval = 2*(1-cdfnorm(abs(tstat))). compute temp = obs-abs(xp2)*cfse. compute outp = {outp, cfse, tstat, pval, temp}. compte temp = obs+abs(xp2)*cfse. compute outp = {outp, temp}. compute clbs = {clbs, "se", "Z", "p", "LLCI", "ULCI"}. compute jnclbs=clbs. end if. end if. do if (boot > 0). compute ones = make(boot,1,1). compute estmte=indboot((1+(im-1)*(boot+1)),:). compute indboot2 = indboot((2+(im-1)*(boot+1)):(1+(im-1)*(boot+1)+boot),:). compute mnind = t(csum(indboot2)/boot). compute stdind=t(sqrt((cssq(indboot2)-((csum(indboot2)&**2)/boot))/(boot-1))). /* here is the sorting algorithm */. compute llci=make(1,ncol(indboot2),-999). compute ulci=make(1,ncol(indboot2),-999). loop #e = 1 to ncol(indboot2). bcboot databcbt = indboot2(:,#e)/estmte=(estmte(1,#e)*bconoff)+(9999*(1-bconoff)). compute llci(1,#e)=llcit. compute ulci(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. compute outp = {modvals, obs, stdind, t(llci), t(ulci)}. compute clbs = {modvnm, "Effect", "Boot SE", "BootLLCI", "BootULCI"}. end if. compute mtemp = mnames(1, im). compute rlbs = make(nrow(modvals),1,mnames(1,im)). do if (model < 4). do if (coeffci = 0). compute outp = outp(:,1:(ncol(outp)-2)). end if. print outp/title = "Conditional effect of X on Y at values of the moderator(s):"/cnames = clbs/format = !decimals. end if. do if (model > 5 and mod74dic <> 1). do if (im = 1). print/title = "Conditional indirect effect(s) of X on Y at values of the moderator(s):". end if. print outp/title = "Mediator"/rnames = rlbs/cnames = clbs/format = !decimals. else if (mod74dic = 1 and model = 74). do if (im = 1). print/title = "Indirect effect(s) of X on Y:". compute clbs3=clbs(1,2:ncol(clbs)). end if. compute outp3=outp(1,2:ncol(outp)). print outp3/title = "Mediator"/rnames = rlbs/cnames = clbs3/format = !decimals. end if. end loop. loop i = notes to 1 by -1. do if (note(i,1) = 4). print/title = "Values for quantitative moderators are 10th, 25th, 50th, 75th, and 90th "+ "percentiles.". print/title = "Values for dichotomous moderators are the two values of the "+ "moderator."/space=0. end if. do if (note(i,1) = 5). print/title = "Values for quantitative moderators are the mean and plus/minus one SD "+ "from mean.". print/title = "Values for dichotomous moderators are the two values of the "+ "moderator."/space=0. end if. do if (note(i,1) = 14). print/title = "NOTE: For at least one moderator in the conditional effects table above, "+ "one SD ". print/title = " below the mean was replaced with the minimum because one SD below "+ "the mean"/space=0. print/title = " is outside of the range of the data."/space=0. end if. do if (note(i,1) = 15). print/title = "NOTE: For at least one moderator in the conditional effects table above, "+ "one SD ". print/title = " above the mean was replaced with the maximum because one SD above "+ "the mean"/space=0. print/title = " is outside of the range of the data."/space=0. end if. end loop. do if (model = 3). compute jnvals=make(nrow(matw),7,0). compute jnvals(:,1)=matw. compute jnvals(:,2)=jnb1+jnb3*jnvals(:,1). compute jnvals(:,3)=sqrt(jnsb1+2*jnvals(:,1)*jnsb1b3+(jnvals(:,1)&*jnvals(:,1))* jnsb3). compute jnvals(:,4)=jnvals(:,2)&/jnvals(:,3). do if (dichy = 0). compute jnvals(:,5)=2*(1-tcdf(abs(jnvals(:,4)), jndf)). end if. do if (dichy = 1). compute jnvals(:,5)=2*(1-cdfnorm(abs(jnvals(:,4)))). end if. compute jnvals(:,6)=jnvals(:,2)-sqrt(jncrit)&*jnvals(:,3). compute jnvals(:,7)=jnvals(:,2)+sqrt(jncrit)&*jnvals(:,3). compute clbs={clbs(:,1),clbs(:,3:ncol(clbs))}. do if (coeffci = 0). compute jnvals =jnvals(:,1:(ncol(jnvals)-2)). end if. print jnvals/title = "Conditional effect of X*M interaction at values of W:"/cnames =clbs/format = !decimals. end if. do if (jn = 1 and (model = 1 or model = 3) and jndich = 0). print/title = "********************* JOHNSON-NEYMAN TECHNIQUE **************************". compute ajn =(jncrit*jnsb3)-(jnb3*jnb3). compute bjn = 2*((jncrit*jnsb1b3)-(jnb1*jnb3)). compute cjn = (jncrit*jnsb1)-(jnb1*jnb1). compute radarg = (bjn*bjn)-(4*ajn*cjn). compute den = 2*ajn. compute nrts = 0. do if (radarg >= 0 and den <> 0). compute x21 = (-bjn+sqrt(radarg))/den. compute x22 = (-bjn-sqrt(radarg))/den. compute roots = 0. do if (x21 >= jnmin and x21 <= jnmax). compute nrts = 1. compute roots = {roots; x21}. end if. do if (x22 >= jnmin and x22 <= jnmax). compute nrts = nrts + 1. compute roots = {roots; x22}. end if. compute roots={roots,make(nrow(roots),2,0)}. compute modtemp=m. do if (model=3). compute modtemp=w. end if. do if (nrts > 0). compute roots = roots(2:nrow(roots),1:3). compute roots(1,2)=(csum(modtemp < roots(1,1))/n)*100. compute roots(1,3)=(csum(modtemp > roots(1,1))/n)*100. do if (nrow(roots)=2). compute roots(2,2)=(csum(modtemp < roots(2,1))/n)*100. compute roots(2,3)=(csum(modtemp > roots(2,1))/n)*100. end if. print roots/title = "Moderator value(s) defining Johnson-Neyman significance "+ "region(s):"/clabels = "Value", "% below", "% above"/format = !decimals. compute jnvals=make((21+nrts),7,0). loop i= 0 to 20. compute jnvals((i+1),1)=jnmin+(i*((jnmax-jnmin)/20)). end loop. loop i = 1 to nrts. loop j = 2 to nrow(jnvals). do if ((roots(i,1) > jnvals((j-1),1)) and (roots(i,1) < jnvals(j,1))). compute jnvals((j+1):(21+i),1)=jnvals(j:(20+i),1). compute jnvals(j,1)=roots(i,1). end if. end loop. end loop. loop i = 1 to nrow(jnvals). compute jnvals(i,2)=jnb1+jnb3*jnvals(i,1). compute jnvals(i,3)=sqrt(jnsb1+2*jnvals(i,1)*jnsb1b3+(jnvals(i,1)*jnvals(i,1))* jnsb3). compute jnvals(i,4)=jnvals(i,2)/jnvals(i,3). do if (dichy = 0). compute jnvals(i,5)=2*(1-tcdf(abs(jnvals(i,4)), jndf)). end if. do if (dichy = 1). compute jnvals(i,5)=2*(1-cdfnorm(abs(jnvals(i,4)))). end if. compute jnvals(i,6)=jnvals(i,2)-sqrt(jncrit)*jnvals(i,3). compute jnvals(i,7)=jnvals(i,2)+sqrt(jncrit)*jnvals(i,3). end loop. do if (model = 1). print jnvals/title = "Conditional effect of X on Y at values of the moderator "+ "(M)"/cnames =jnclbs/format = !decimals. end if. do if (model = 3). compute jnclbs={jnclbs(:,1),jnclbs(:,3:ncol(jnclbs))}. print jnvals/title = "Conditional effect of X*M on Y at values of the moderator "+ "(W)"/cnames =jnclbs/format = !decimals. end if. end if. do if (nrts = 0). print/title = "There are no statistical significance transition points within the "+ "observed range of the moderator". end if. else. print/title = "There are no statistical significance transition points within the "+ "observed range of the moderator". end if. end if. end if. /* print data for plotting */. do if (model < 4 and plot = 1). compute dataplot = make((nrow(modvals)*nrow(matx)),(ncol(modvals)+1),0). compute tmp = 1. loop i = 1 to nrow(modvals). loop j = 1 to nrow(matx). compute dataplot(tmp,:)={matx(j,1), modvals(i,:)}. compute tmp=tmp+1. end loop. end loop. compute dataplot = {dataplot, make(nrow(dataplot),(1+dichy),0)}. compute dataplo2 = make(nrow(dataplot),1,1). do if (model = 1). compute dataplo2 = {dataplo2, dataplot(:,2), dataplot(:,1), (dataplot(:,1)&*dataplot(:,2))}. end if. do if (model = 2 or model = 3). compute dataplo2 = {dataplo2, dataplot(:,3), dataplot(:,1), (dataplot(:,1)&*dataplot(:,3)), dataplot(:,2), (dataplot(:,1)&*dataplot(:,2))}. do if (model = 3). compute dataplo2 = {dataplo2, (dataplot(:,2)&*dataplot(:,3)), (dataplot(:,1)&*dataplot(:,2)&*dataplot(:,3))}. end if. end if. loop i = 1 to nrow(dataplot). compute tmp=dataplo2(i,:). do if (ncovs > 0). compute tmp = {tmp, covmeans}. end if. do if (cluster > 0). compute tmp = {tmp, cldmeans}. end if. compute dataplot(i,(ncol(dataplot)-(dichy)))=tmp*coeffplt. do if (dichy = 1). compute dataplot(i,(ncol(dataplot)))=exp(tmp*coeffplt)/(1+exp(tmp*coeffplt)). end if. end loop. compute clbs = {xname, modvnm, "yhat"}. do if (dichy = 1). compute clbs = {xname, modvnm, "ln(odds)", "prob"}. end if. print/title = "**************************************************************************". print dataplot/title = "Data for visualizing conditional effect of X of Y:"/cnames = clbs/format = !decimals. do if (ncovs > 0). print/title = "Estimates in this table are based on setting covariates to their sample "+ "means". end if. end if. end if. do if (model = 7 or model = 8 or model = 12 or model = 14 or model = 15 or (model = 74 and mod74dic=0) or ((model = 58 or model = 59) and wvdich=1)). compute obsprod = t(indbootp(1,:)). do if (boot > 0). compute ones = make(boot,1,1). compute estmte=indbootp(1,:). compute indbootp = indbootp(2:(boot+1),:). compute mnindp = t(csum(indbootp)/boot). compute stdindp=t(sqrt((cssq(indbootp)-((csum(indbootp)&**2)/boot))/(boot-1))). compute llcip=make(1,ncol(indbootp),-999). compute ulcip=make(1,ncol(indbootp),-999). loop #e = 1 to ncol(indbootp). bcboot databcbt = indbootp(:,#e)/estmte=(estmte(1,#e)*bconoff)+(9999*(1-bconoff)). compute llcip(1,#e)=llcit. compute ulcip(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. compute outp = {obsprod, stdindp, t(llcip), t(ulcip)}. compute clbs = {"Effect", "SE(Boot)", "BootLLCI", "BootULCI"}. do if (model = 8 or model = 12). print/title="-----". print/title = "Indirect effect of highest order interaction:"/space=0. print outp/title = "Mediator"/cnames = clbs/rnames = mnames/format = !decimals. end if. do if (model <> 12). print/title = "******************** INDEX OF MODERATED MEDIATION ************************". compute clbs3 = {"Index", "SE(Boot)", "BootLLCI", "BootULCI"}. print outp/title = "Mediator"/cnames = clbs3/rnames = mnames/format = !decimals. do if (wvdich=1). print/title = "When the moderator is dichotomous, this is a test of equality of the". print/title = "conditional indirect effects in the two groups."/space=0. end if. end if. end if. do if (boot = 0). do if (model = 8 or model = 12). print/title="-----". print/title = "Indirect effect of highest order interaction:"/space=0. print obsprod/title = "Mediator"/clabels = "Effect"/rnames = mnames/format = !decimals. end if. do if (model <> 12). print/title = "******************** INDEX OF MODERATED MEDIATION ************************". print obsprod/title = "Mediator"/clabels = "Index"/rnames = mnames/format = !decimals. end if. end if. end if. compute conmake=0. compute concols=0. do if ((model > 3 and model < 7) and (contrast = 1) and nmods = 0 and nmeds > 1 ). compute concols = ((ncol(indboot)*(ncol(indboot)-1))/2). compute indcon=make(nrow(indboot),concols,-999). compute conkey = {" ", " ", " "}. compute temp=1. compute conmake=1. loop i = 1 to (ncol(indboot)-1). loop j = (i+1) to (ncol(indboot)). compute indcon(:,temp)=indboot(:,i)-indboot(:,j). do if (model <> 6). compute conkey={conkey; mnames(1,i), "minus", mnames(1,j)}. end if. do if (model = 6). compute conkey={conkey; indlbl2(i,1), "minus", indlbl2(j,1)}. end if. compute temp=temp+1. end loop. end loop. end if. do if (model = 4 or model = 5). compute clbs = {"Effect"}. compute rlbs = {"TOTAL"; t(mnames)}. compute obs = t(indboot(1,:)). compute obs = {csum(obs); obs}. do if (conmake = 1). compute obs={obs; t(indcon(1,:))}. compute rlbs = {rlbs; cntname(1:ncol(indcon),1)}. end if. compute outp = obs. compute outp2=outp. do if (effsize = 1 and dichy = 0 and ncovs = 0). compute pmeff(:,1)=rsum(pmeff(:,2:ncol(pmeff))). compute rmeff(:,1)=rsum(rmeff(:,2:ncol(rmeff))). compute abpseff(:,1)=rsum(abpseff(:,2:ncol(abpseff))). compute abcseff(:,1)=rsum(abcseff(:,2:ncol(abcseff))). compute eff = {pmeff, rmeff, abpseff, abcseff}. do if (nmeds = 1 and ncovs = 0 and cluster = 0 and model = 4). compute eff = {eff, r245, kappa2}. compute r245obs = {r245(1,1);r245(1,1)}. compute kappa2ob = kappa2(1,1). end if. compute pmobs = t(pmeff(1,1:(nmeds+1))). compute rmobs = t(rmeff(1,1:(nmeds+1))). compute psobs = t(abpseff(1,1:(nmeds+1))). compute csobs = t(abcseff(1,1:(nmeds+1))). do if (contrast = 0). compute outp2 = {obs, psobs, csobs, pmobs, rmobs}. end if. do if (contrast = 1). compute obs2=obs(1:nrow(psobs),:). compute outp2 = {obs2, psobs, csobs, pmobs, rmobs}. end if. compute clbs = {"ab", "ab_ps", "ab_cs", "ab/c", "ab/c'"}. do if (nmeds = 1 and ncovs = 0 and cluster = 0 and model = 4). compute outp2 = {outp2, r245obs, (obs/abmmr)}. compute clbs = {clbs, "R-sq_med", "kappa2"}. end if. end if. do if (boot = 0). do if (nmeds = 1). compute outp2 = outp2(2,:). compute rlbs = rlbs(2,1). end if. print outp2/title = "Indirect effect(s) of X on Y"/rnames = rlbs/cnames = clbs/format = !decimals. do if (contrast = 1 and effsize = 1 and nmeds > 1). compute outp2=t(indcon(1,:)). compute rlbs2 = cntname(1:ncol(indcon),1). print outp2/title = "Contrast(s) between indirect effects"/rnames = rlbs2/cnames=clbs/format = !decimals. end if. end if. do if (boot > 0). compute ones = make(boot,1,1). compute indboot = {rsum(indboot), indboot}. do if (conmake = 1). compute indboot={indboot, indcon}. end if. compute estmte=indboot(1,:). compute indboot = indboot(2:(boot+1),:). compute mnind = t(csum(indboot)/boot). compute stdind=t(sqrt((cssq(indboot)-((csum(indboot)&**2)/boot))/(boot-1))). compute llci=make(1,ncol(indboot),-999). compute ulci=make(1,ncol(indboot),-999). loop #e = 1 to ncol(indboot). bcboot databcbt=indboot(:,#e)/estmte = (estmte(1,#e)*bconoff)+(9999*(1-bconoff)). compute llci(1,#e)=llcit. compute ulci(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. do if (effsize = 1 and dichy = 0 and ncovs = 0). compute estmte=eff(1,:). compute eff = eff(2:nrow(eff),:). compute stdindf=t(sqrt((cssq(eff)-((csum(eff)&**2)/boot))/(boot-1))). compute llcif=make(1,ncol(eff),-999). compute ulcif=make(1,ncol(eff),-999). loop #e = 1 to ncol(eff). bcboot databcbt=eff(:,#e)/estmte = (estmte(1,#e)*bconoff)+(9999*(1-bconoff)). compute llcif(1,#e)=llcit. compute ulcif(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. end if. /* end of sorting algorithm */. end if. do if (boot > 0). compute outp = {obs, stdind, t(llci), t(ulci)}. do if (nmeds = 1). compute outp = outp(2,:). compute rlbs = rlbs(2,1). end if. compute clbs = {"Effect", "Boot SE", "BootLLCI", "BootULCI"}. print outp/title = "Indirect effect of X on Y"/rnames = rlbs/cnames = clbs/format = !decimals. do if (dichy = 0 and effsize = 1 and ncovs = 0). compute outp = {psobs, stdindf((2*(nmeds+1)+1) :(3*(nmeds+1)),1), t(llcif(1,(2*(nmeds+1)+1):(3*(nmeds+1)))), t(ulcif(1,(2*(nmeds+1)+1):(3*(nmeds+1))))}. do if (nmeds = 1). compute outp = outp(2,:). end if. print outp/title = "Partially standardized indirect effect of X on Y"/rnames = rlbs/cnames clbs/format = !decimals. compute outp = {csobs, stdindf((3*(nmeds+1)+1): (4*(nmeds+1)),1), t(llcif(1,(3*(nmeds+1)+1):(4*(nmeds+1)))), t(ulcif(1,(3*(nmeds+1)+1):(4*(nmeds+1))))}. do if (nmeds = 1). compute outp = outp(2,:). end if. print outp/title = "Completely standardized indirect effect of X on Y"/rnames = rlbs/cnames clbs/format = !decimals. compute outp = {pmobs, stdindf(1:(nmeds+1),1),t(llcif(1,1:(nmeds+1))), t(ulcif(1,1:(nmeds+1))) }. do if (nmeds = 1). compute outp = outp(2,:). end if. print outp/title = "Ratio of indirect to total effect of X on Y"/rnames = rlbs/cnames = clbs/format = !decimals. compute outp = {rmobs, stdindf(((nmeds+1)+1) :(2*(nmeds+1)) ,1), t(llcif(1,((nmeds+1)+1):(2*(nmeds+1)))), t(ulcif(1,((nmeds+1)+1):(2*(nmeds+1))))}. do if (nmeds = 1). compute outp = outp(2,:). end if. print outp/title = "Ratio of indirect to direct effect of X on Y"/rnames = rlbs/cnames = clbs/format = !decimals. do if (nmeds = 1 and cluster = 0 and ncovs = 0 and model = 4). compute r245obs = r245obs(1,1). compute outp = {r245obs, stdindf((4*(nmeds+1)+1) :(4*(nmeds+1)+1),1), t(llcif(1,(4*(nmeds+1)+1):(4*(nmeds+1)+1))), t(ulcif(1,(4*(nmeds+1)+1):(4*(nmeds+1)+1)))}. print outp/title = "R-squared mediation effect size (R-sq_med)"/rnames = rlbs/cnames = clbs/format = !decimals. compute outp = {kappa2ob, stdindf(nrow(stdindf),1),llcif(1,ncol(llcif)), ulcif(1,ncol(ulcif))}. print outp/title = "Preacher and Kelley (2011) Kappa-squared"/rnames = rlbs/cnames = clbs/format = !decimals. end if. end if. end if. do if (normal = 1). do if (nmeds = 1). print sobel/title = "Normal theory tests for indirect effect"/clabels = "Effect", "se", "Z", "p"/format = !decimals. end if. do if (nmeds > 1). compute rlbs2 = rlbs(2:nrow(rlbs),1). print sobel/title = "Normal theory tests for specific indirect effects"/rnames = rlbs2/clabels = "Effect", "se", "Z", "p"/format = !decimals. end if. end if. do if (conmake = 1). compute conkey=conkey(2:nrow(conkey),:). compute conlbs = cntname(1:ncol(indcon),1). print conkey/title = "Specific indirect effect contrast definitions"/rnames = conlbs/format = A10. end if. end if. do if (model = 6). compute clbs = {"eff"}. compute rlbs = {"TOTAL"; t(mnames)}. compute obs = t(indboot(1,:)). compute obs = {csum(obs); obs}. compute indlbl = indlbl(1:nrow(obs),1). do if (conmake = 1). compute obs={obs; t(indcon(1,:))}. compute indlbl = {indlbl; cntname(1:ncol(indcon),1)}. end if. compute obs2=obs. do if (boot = 0). do if (dichy = 0 and effsize = 1 and ncovs = 0). compute obs = {obs, obs/stddevy, (obs*stddevx/stddevy), obs/ctot, obs/mmpaths(nrow(mmpaths),1)}. compute clbs = {"eff", "eff_ps", "eff_cs", "eff/c", "eff/c'"}. compute obs2=obs. do if (contrast = 1). compute obs2 = obs(1:(nrow(obs)-concols),:). end if. end if. print obs2/title = "Indirect effect(s) of X on Y"/rnames = indlbl/cnames = clbs/format = !decimals. do if (contrast = 1 and effsize = 1). compute outp2=t(indcon(1,:)). compute rlbs2 = cntname(1:ncol(indcon),1). print outp2/title = "Contrast(s) between indirect effects"/rnames = rlbs2/cnames=clbs/format = !decimals. end if. end if. do if (boot > 0). compute ones = make(boot,1,1). compute indboot = {rsum(indboot), indboot}. do if (conmake = 1). compute indboot={indboot, indcon}. end if. compute estmte=indboot(1,:). compute indboot = indboot(2:(boot+1),:). compute mnind = t(csum(indboot)/boot). compute stdind=t(sqrt((cssq(indboot)-((csum(indboot)&**2)/boot))/(boot-1))). compute temp = nrow(indboot). compute llci=make(1,ncol(indboot),-999). compute ulci=make(1,ncol(indboot),-999). loop #e = 1 to ncol(indboot). bcboot databcbt = indboot(:,#e)/estmte=(estmte(1,#e)*bconoff)+(9999*(1-bconoff)). compute llci(1,#e)=llcit. compute ulci(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. compute obs = {obs, stdind, t(llci), t(ulci)}. compute clbs = {"Effect", "Boot SE", "BootLLCI", "BootULCI"}. print obs/title = "Indirect effect(s) of X on Y"/rnames = indlbl/cnames = clbs/format = !decimals. do if (effsize = 1 and dichy = 0 and ncovs = 0). compute indboot=indboot(:,1:(ncol(indboot)-concols)). compute eff = {rsum(abpseff), abpseff, rsum(abcseff), abcseff, rsum(pmeff), pmeff, rsum(rmeff), rmeff}. compute effobs = eff(1,:). compute eff = eff(2:nrow(eff),:). compute stdindf=t(sqrt((cssq(eff)-((csum(eff)&**2)/boot))/(boot-1))). compute llcif=make(1,ncol(eff),-999). compute ulcif=make(1,ncol(eff),-999). loop #e = 1 to ncol(eff). bcboot databcbt =eff(:,#e)/estmte = (effobs(1,#e)*bconoff)+(9999*(1-bconoff)). compute llcif(1,#e)=llcit. compute ulcif(1,#e)=ulcit. do if (badlo = 1 and llcit <> priorlo). compute badend={badend, llcit}. compute priorlo = llcit. end if. do if (badhi = 1 and ulcit <> priorhi). compute badend={badend, ulcit}. compute priorhi = ulcit. end if. end loop. compute temp2 = stdindf(1:ncol(indboot),1). compute temp3 = effobs(:,1:ncol(indboot)). compute templow = llcif(1,1:ncol(indboot)). compute temphi = ulcif(1,1:ncol(indboot)). compute outp = {t(temp3), temp2,t(templow), t(temphi)}. print outp/title = "Partially standardized indirect effect of X on Y"/cnames = clbs/rnames indlbl/format = !decimals. compute temp2 = stdindf((ncol(indboot)+1):(2*ncol(indboot)),1). compute temp3 = effobs(:,(ncol(indboot)+1):(2*ncol(indboot))). compute templow = llcif(1,(ncol(indboot)+1):(2*ncol(indboot))). compute temphi = ulcif(1,(ncol(indboot)+1):(2*ncol(indboot))). compute outp = {t(temp3), temp2,t(templow), t(temphi)}. print outp/title = "Completely standardized indirect effect of X on Y"/cnames = clbs/rnames indlbl/format = !decimals. compute temp2 = stdindf((2*(ncol(indboot))+1):(3*ncol(indboot)),1). compute temp3 = effobs(:,(2*(ncol(indboot))+1):(3*ncol(indboot))). compute templow = llcif(1,(2*(ncol(indboot))+1):(3*ncol(indboot))). compute temphi = ulcif(1,(2*(ncol(indboot))+1):(3*ncol(indboot))). compute outp = {t(temp3), temp2,t(templow), t(temphi)}. print outp/title = "Ratio of indirect to total effect of X on Y"/rnames = indlbl/cnames = clbs/format = !decimals. compute temp = eff(:,(3*(ncol(indboot))+1):(4*ncol(indboot))). compute temp2 = stdindf((3*(ncol(indboot))+1):(4*ncol(indboot)),1). compute temp3 = effobs(:,(3*(ncol(indboot))+1):(4*ncol(indboot))). compute templow = llcif(1,(3*(ncol(indboot))+1):(4*ncol(indboot))). compute temphi = ulcif(1,(3*(ncol(indboot))+1):(4*ncol(indboot))). compute outp = {t(temp3), temp2,t(templow), t(temphi)}. print outp/title = "Ratio of indirect to direct effect of X on Y"/rnames = indlbl/cnames = clbs/format = !decimals. end if. end if. do if (nmeds = 2). compute effkey = {xname, "->", mnames(1,1), "->", yname, " ", " "}. compute effkey = {effkey; xname, "->", mnames(1,1), "->", mnames(1,2), "->", yname}. compute effkey = {effkey; xname, "->", mnames(1,2), "->", yname, " ", " "}. compute effkey = {indlbl(2:4,1), effkey}. end if. do if (nmeds = 3). compute effkey = {xname, "->" , mnames(1,1), "->", yname, " ", " ", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", yname, " ", " "+ ""}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,3), "->", yname, " ", " "+ ""}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", mnames(1,3), "->", yname}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", yname, " ", " ", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", mnames(1,3), "->", yname, " ", " "+ ""}. compute effkey = {effkey; xname, "->" , mnames(1,3), "->", yname, " ", " ", " ", " "}. compute effkey = {indlbl(2:8,1), effkey}. end if. do if (nmeds = 4). compute effkey = {xname, "->" , mnames(1,1), "->", yname, " ", " ", " ", " ", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,3), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,4), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", mnames(1,3), "->", yname, " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", mnames(1,4), "->", yname, " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,3), "->", mnames(1,4), "->", yname, " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,1), "->", mnames(1,2), "->", mnames(1,3), "->", mnames(1,4), "->", yname}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", yname, " ", " ", " ", " ", " ", " "+ ""}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", mnames(1,3), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", mnames(1,4), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,2), "->", mnames(1,3), "->", mnames(1,4), "->", yname, " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,3), "->", yname, " ", " ", " ", " ", " ", " "+ ""}. compute effkey = {effkey; xname, "->" , mnames(1,3), "->", mnames(1,4), "->", yname, " ", " "+ "", " ", " "}. compute effkey = {effkey; xname, "->" , mnames(1,4), "->", yname, " ", " ", " ", " ", " ", " "+ ""}. compute effkey = {indlbl(2:16,1), effkey}. end if. print effkey/title = "Indirect effect key"/format = A8. do if (conmake = 1). compute conkey=conkey(2:nrow(conkey),:). compute conlbs = cntname(1:ncol(indcon),1). print conkey/title = "Specific indirect effect contrast definitions"/rnames = conlbs/format = A10. end if. end if. end if. do if (bad > 0). compute note(notes,1) = 9. compute notes = notes + 1. end if. print/title = "******************** ANALYSIS NOTES AND WARNINGS *************************". loop i = 1 to errs. do if (runerrs(i,1) = 1). print/title = "ERROR: One of your declared mediators is dichotomous. This procedure can't "+ "be used.". end if. do if (runerrs(i,1) = 2). print/title = "ERROR: For model 6, this procedure limits the number of mediators to four.". end if. do if (runerrs(i,1) = 3). print/title = "ERROR: For models 1, 2, and 3, only a single variable can be listed in the M "+ "list.". end if. do if (runerrs(i,1) = 4). print/title = "ERROR: You requested a model involving W but did not provide a valid W "+ "variable name.". end if. do if (runerrs(i,1) = 5). print/title = "ERROR: You requested a model involving Z but did not provide a valid Z "+ "variable name.". end if. do if (runerrs(i,1) = 6). print/title = "ERROR: You requested a model involving Q but did not provide a valid Q "+ "variable name.". end if. do if (runerrs(i,1) = 7). print/title = "ERROR: You requested a model involving V but did not provide a valid V "+ "variable name.". end if. do if (runerrs(i,1) = 8). print/title = "ERROR: You specified a W variable for a model that does not need it". end if. do if (runerrs(i,1) = 9). print/title = "ERROR: You specified a Z variable for a model that does not need it". end if. do if (runerrs(i,1) = 10). print/title = "ERROR: You specified a Q variable for a model that does not need it". end if. do if (runerrs(i,1) = 11). print/title = "ERROR: You specified a V variable for a model that does not need it.". end if. do if (runerrs(i,1) = 12). print/title = "ERROR: The variable specified for W has already been assigned.". end if. do if (runerrs(i,1) = 13). print/title = "ERROR: The variable specified for Z has already been assigned.". end if. do if (runerrs(i,1) = 14). print/title = "ERROR: The variable specified for Q has already been assigned.". end if. do if (runerrs(i,1) = 15). print/title = "ERROR: The variable specified for V has already been assigned.". end if. do if (runerrs(i,1) = 16). print/title = "ERROR: You did not provide a valid Y variable name.". end if. do if (runerrs(i,1) = 17). print/title = "ERROR: The variable specified for Y has already been assigned.". end if. do if (runerrs(i,1) = 18). print/title = "ERROR: Model 6 requires more than one mediator.". end if. do if (runerrs(i,1) = 19). print/title = "ERROR: You have not specified a valid model number.". end if. do if (runerrs(i,1) = 20). print/title = "ERROR: At least one and only one variable can be listed for X.". end if. do if (runerrs(i,1) = 21). print/title = "ERROR: At least one and only one variable can be listed for Y.". end if. do if (runerrs(i,1) = 22). print/title = "ERROR: Iteration didn't converge to a solution. Interpret results with "+ "caution.". end if. do if (runerrs(i,1) = 23). print/title = "ERROR: Your specified a clustering variable that does not exist in your "+ "variable list.". end if. do if (runerrs(i,1) = 24). print/title = "ERROR: You specified a clustering variable that has already been assigned.". end if. do if (runerrs(i,1) = 25). print/title = "ERROR: One or more of your M variables is not listed in the variables list.". end if. do if (runerrs(i,1) = 26). print/title = "ERROR: A maximum of 20 cluster units is allowed. Use multilevel modeling "+ "instead.". end if. do if (runerrs(i,1) = 27). print/title = "ERROR: One of the variables in your model is a constant.". end if. end loop. do if (errs = 0). do if (boot > 1). do if (bconoff = 1). print boot/title = "Number of bootstrap samples for bias corrected bootstrap confidence "+ "intervals:"/format = F8.0. end if. do if (bconoff = 0). print boot/title = "Number of bootstrap samples for percentile bootstrap confidence "+ "intervals:"/format = F8.0. end if. do if (booterr = 1). compute badend = badend(1,2:ncol(badend)). print badend/title = "WARNING: Bootstrap CI endpoints below not trustworthy. Decrease "+ "confidence or increase bootstraps"/format = !decimals. end if. end if. print conf/title = "Level of confidence for all confidence intervals in output:"/format = F8.2. do if (center = 1 and (ncol(centvar) > 1)). compute centvar = centvar(1,2:ncol(centvar)). print centvar/title = "NOTE: The following variables were mean centered prior to "+ "analysis:"/format = a8. end if. loop i = 1 to notes. do if (note(i,1) = 1). print/title = "NOTE: Confidence level restricted to between 50 and 99.9999%. 95% "+ "confidence is provided in output". end if. do if (note(i,1) = 2). print/title = "NOTE: Effect size measures for indirect effects not available for models "+ "with dichotomous outcomes". end if. do if (note(i,1) = 3). print/title = "NOTE: All standard errors for continuous outcome models are based on the "+ "HC3 estimator". end if. do if (note(i,1) = 6). print/title = "NOTE: The number of bootstrap samples was adjusted upward given your "+ "desired confidence". end if. do if (note(i,1) = 7). print/title = "NOTE: The Johnson-Neyman method is available only for Models 1 and 3". end if. do if (note(i,1) = 8). print/title = "NOTE: The Johnson-Neyman method cannot be used with a dichotomous moderator". end if. do if (note(i,1)=9). print bad/title = "NOTE: Some bootstrap samples had to be replaced. The number of such "+ "replacements was:". end if. do if (note(i,1) = 10). print/title = "NOTE: Effect size measures for indirect effects not available for models "+ "with covariates". end if. do if (note(i,1) = 11). print nmiss/title = "NOTE: Some cases were deleted due to missing data. The number of "+ "such cases was:". end if. end loop. end if. end matrix. match files/file = */drop = w999999t z999999t q999999t v999999t. execute. set printback=on. !enddefine. PROCESS vars = lgTotal_cal Low_vs_average_dummy lgFeedback_concern lgTime_taken_for_ad_lib High_vs_average_dummy /y=lgTotal_cal/x=Low_vs_average_dummy/m=lgFeedback_concern lgTime_taken_for_ad_lib/w=/z=/v=/q=/ model =6/boot=10000/center=0/hc3=0/effsize=0/ normal=0/coeffci=1/conf=95/percent=0/total=1/ covmy=0/jn=0/quantile =0/plot=0/contrast=0/ decimals=F10.4.