Hello I wish to call the following macro and run the analysis below. The macro runs well but the last part to simulate a data and runs does not work. Any help?
The problem is from the data test (marked bold below) , no problem with the macro. The error is at the tail end
%macro indirect(data=,y=,x=,m=,c=0,boot=1000,conf=95,percent=0,bc=1,bca=0, normal=0,contrast=0);
proc iml;
use &data;
read all var{&y &x &m} into dd;
nm={&y &x &m};
xx=(dd = .);xx=xx[,+];
j=1;do i = 1 to nrow(dd);if xx[i,1]=0 then;do;dd[j,]=dd[i,];j=j+1;end;end;
dd=dd[1:j-1,];
nm = nm`;
n = nrow(dd);
nv = ncol(dd);
nc = &c;
con=j(n,1,1);
dt2 = dd;
dt = dd;
resid = j(n,(nv-nc),0);
info = j((2*(nv-nc-2)+1),(2*(nv-nc-2)+1),0);
imat = j(ncol(info),4,1);
imat[1:(nv-nc-2),1]=(2:(nv-nc-1))`;
imat[1:(nv-nc-2),3]=(2:(nv-nc-1))`;
imat[(nv-nc-1):(ncol(info)-1),2]=(2:(nv-nc-1))`;
imat[(nv-nc-1):(ncol(info)-1),4]=(2:(nv-nc-1))`;
imat[(nv-nc-1):(ncol(info)-1),1]=j((nv-nc-2),1,(nv-nc));
imat[(nv-nc-1):(ncol(info)-1),3]=j((nv-nc-2),1,(nv-nc));
imat[ncol(info),1:4]={1 1 1 1};
imat[ncol(info),1]=nv-nc;
imat[ncol(info),3]=nv-nc;
bzx = j(nv-2-nc,1,0);
bzxse = j(nv-2-nc,1,0);
b=j((nv-1-nc),(nv-1-nc),0);
cname={"C1", "C2", "C3", "C4", "C5", "C6", "C7", "C8", "C9", "C10", "C11", "C12", "C13", "C14", "C15", "C16"};
cname=cname//{"C17", "C18", "C19", "C20", "C21", "C22", "C23", "C24", "C25", "C26", "C27", "C28", "C29"};
cname=cname//{"C30", "C31", "C32", "C33", "C34", "C35", "C36", "C37", "C38", "C39", "C40", "C41", "C42"};
cname=cname//{"C43", "C44", "C45"};
p0 = -0.322232431088;
p1 = -1;
p2 = -0.342242088547;
p3 = -0.0204231210245;
p4 = -.0000453642210148;
q0 = 0.0993484626060;
q1 = 0.588581570495;
q2 = 0.531103462366;
q3 = 0.103537752850;
q4 = 0.0038560700634;
conf=round(&conf);
lowalp = 0.5*(1-(conf/100));
upalp = 0.5*(1+(conf/100));
zbca = lowalp//upalp;
btn = 1;
if (&boot > 999) then;
do;
btn = floor(&boot/1000)*1000;
end;
blowp = floor(lowalp*btn);
if (blowp < 1) then;
do;
blowp = 1;
end;
bhighp = floor((upalp*btn)+1);
if (bhighp > btn) then;
do;
bhighp = btn;
end;
indeff = j((n+1+btn),(nv-1-nc),0);
do d = 1 to (n+1+btn);
if (d = (n+2)) then;
do;
dt = dt2;
con = j(n,1,1);
end;
if (d > 1) then if (d < (n+2)) then;
do;
if (d = 2) then;
do;
con = j((n-1),1,1);
dt = dt2[2:n,];
end;
if (d = (n+1)) then;
do;
dt = dt2[1:(n-1),];
end;
if (d > 2) then if (d < (n+1)) then;
do;
dt = dt2[1:(d-2),]//dt2[(d:n),];
end;
end;
if (d > (n+1)) then;
do;
do nn = 1 to n;
v = int(ranuni(0)*n)+1;
dt[nn,1:nv]=dt2[v,1:nv];
end;
end;
x = dt[,2];
m = dt[,3:(nv-nc)];
y = dt[,1];
xz = dt[,2:nv];
xo = con||x;
if (nc > 0) then;
do;
c = dt[,(nv-nc+1):nv];
xo = xo||c;
end;
do k = 3 to (nv-nc);
ytmp = dt[,k];
bzxt = inv(xo`*xo)*xo`*ytmp;
bzx[(k-2),1]=bzxt[2,1];
if (d = 1) then;
do;
resid[,(k-1)]=ytmp-(xo*bzxt);
mse = sum((ytmp-(xo*bzxt))##2)/(n-2-nc);
olscm = (mse*inv(xo`*xo));
bzxse[(k-2),1]=sqrt(olscm[2,2]);
end;
end;
if (d = 1) then;
do;
if (nc > 0) then;
do;
cnt = dd[,(nv-(nc-1)):nv];
xo = con||x||cnt;
end;
if (nc = 0) then;
do;
xo = con||x;
end;
byx = inv(xo`*xo)*xo`*y;
mse = sum((y-(xo*byx))##2)/(n-2-nc);
olscm = (mse*inv(xo`*xo));
byxse = sqrt(olscm[2,2]);
byx = byx[2,1];
end;
xzo = con||xz;
byzx = inv(xzo`*xzo)*xzo`*y;
byzx2 = byzx[3:(nv-nc),1];
if (d = 1) then;
do;
resid[,ncol(resid)]=y-(xzo*byzx);
mse = sum((y-(xzo*byzx))##2)/(n-nv);
covmat = mse*inv(xzo`*xzo);
olscm = vecdiag(covmat);
sse = mse*(n-nv);
sst = sum((y-(sum(y)/n))##2);
r2 = 1-(sse/sst);
ar2 = 1-(mse/(sst/(n-1)));
fr = ((n-nv)*r2)/((1-r2)*ncol(xz));
pfr = 1-probf(fr,ncol(xz),(n-nv));
if (nc > 0) then;
do;
bcon = byzx[(nv-nc+1):nv,1];
bconse = sqrt(olscm[(nv-nc+1):nv,1]);
end;
byzx2se = sqrt(olscm[3:(nv-nc),1]);
cprime = byzx[2,1];
cprimese=sqrt(olscm[2,1]);
end;
indeff2 = (bzx#byzx2);
zs = (bzx/bzxse)#(byzx2/byzx2se);
temp = t(sum(indeff2)//indeff2);
indeff[d,]=temp;
if (d = 1) then;
do;
vs = nm[1:(nv-nc),1];
rn = {"DV = " "IV = " "MEDS = "};
print "Dependent, Independent, and Proposed Mediator Variables";
print vs [rowname = rn];
if (nc > 0) then;
do;
vs = nm[(nv-nc+1):nv,1];
print "Statistical Controls";
rn = {"CONTROLS="};
print vs [rowname = rn];
end;
print "Sample size";
print n;
nms = nm[3:(nv-nc),1];
te = bzx/bzxse;
df = n-2-nc;
p = 2*(1-probt(abs(te),df));
bzxmat = bzx||bzxse||te||p;
b[2:(nv-1-nc),1]=bzx;
se2 = bzxse#bzxse;
cnm = {"Coeff" "se" "t" "p"};
print "IV to Mediators (a paths)";
print bzxmat [rowname = nms colname = cnm format = 9.4];
te = byzx2/byzx2se;
df = n-nv;
p = 2*(1-probt(abs(te),df));
byzx2mat=byzx2||byzx2se||te||p;
print "Direct Effects of Mediators on DV (b paths)";
print byzx2mat [rowname = nms colname = cnm format = 9.4];
te=byx/byxse;
df = n-2-nc;
p=2*(1-probt(abs(te),df));
byxmat = byx||byxse||te||p;
xnm=nm[2,1];
print "Total effect of IV on DV (c path)";
print byxmat [rowname = xnm colname = cnm format = 9.4];
te=cprime/cprimese;
df = n-nv;
p=2*(1-probt(abs(te),df));
cprimmat = cprime||cprimese||te||p;
print "Direct Effect of IV on DV (c' path)";
print cprimmat [rowname = xnm colname = cnm format = 9.4];
if (nc > 0) then;
do;
df = n-nv;
nms = nm[(nv-nc+1):nv,1];
te=bcon/bconse;
p=2*(1-probt(abs(te),df));
bconmat = bcon||bconse||te||p;
print "Partial Effect of Control Variables on DV";
print bconmat [rowname = nms colname = cnm format = 9.4];
end;
dvms=r2||ar2||fr||ncol(xz)||(n-nv)||pfr;
print "Fit Statistics for DV Model";
cnm = {"R-sq" "adj R-sq" "F" "df1" "df2" "p"};
print dvms [colname = cnm format = 9.4];
if (&normal =^ 0) then;if(&c = 0) then;do;
do;
bmat=j((nv-nc),(nv-nc),0);
bmat[2:(nv-nc-1),1]=bzx;
bmat[(nv-nc),2:(nv-nc-1)]=byzx2`;
bmat[(nv-nc),1]=cprime;
imbinv = inv(i(ncol(bmat))-bmat);
imbtinv = inv(i(ncol(bmat))-bmat`);
resid[,1]=x-(x[+]/n);
psi = (resid`*resid)/(n-1);
invpsi = inv(psi);
ibpsiib = imbinv*psi*imbtinv;
do ic = 1 to ncol(info);
do ic2 = 1 to ncol(info);
info[ic,ic2]=(n-1)*((imbinv[imat[ic2,4],imat[ic,1]]*imbinv[imat[ic,2],imat[ic2,3]])+(ibpsiib[imat[ic2,4],imat[ic,2]]*invpsi[imat[ic,1],imat[ic2,3]]));
end;
end;
varcov=inv(info);
varcov=varcov[1:(2*(nv-nc-2)),1:(2*(nv-nc-2))];
ses = vecdiag(varcov);
avar = ses[1:nrow(bzxse),1];
bvar = ses[(nrow(bzxse)+1):nrow(ses),1];
if ((nv-nc-2) > 1) then;do;if(&contrast = 1) then;do;
prws=j(((nv-nc-2)*(nv-nc-3)/2),1,0);
prwse=prws;
kk=1;
do ic = 1 to (nv-nc-3);
do ic2 = (ic+1) to (nv-nc-2);
vf2=((byzx2[ic,1]##2)*varcov[ic,ic])-(2*byzx2[ic,1]*byzx2[ic2,1]*(varcov[ic,ic2]));
vf2=vf2+((byzx2[ic2,1]##2)*varcov[ic2,ic2])+((bzx[ic,1]##2)*(bvar[ic,1]));
vf2=vf2-(2*bzx[ic,1]*bzx[ic2,1]*covmat[(2+ic),(2+ic2)])+((bzx[ic2,1]##2)*(bvar[ic2,1]));
cnt=indeff2[ic,1]-indeff2[ic2,1];
prws[kk,1]=cnt;
prwse[kk,1]=sqrt(vf2);
kk=kk+1;
end;
end;
cnam2=cname[1:(kk-1),1];
end;end;
dermat=byzx2//bzx;
totse=sqrt((dermat)`*varcov*dermat);
specse = sqrt((byzx2#byzx2)#(avar)+(bzx#bzx)#(bvar));
specse = totse//specse;
indsum=indeff2[+];
specz = (indsum//indeff2)/specse;
ind22 = indsum//indeff2;
nms = {"TOTAL"}//nm[3:(nv-nc),1];
if ((nv-nc-2) > 1) then;do;if(&contrast = 1) then;do;
ind22 = ind22//prws;
specse = specse//prwse;
specz2 = prws/prwse;
specz = specz//specz2;
nms = nms//cnam2;
end;end;
pspec = 2*(1-probnorm(abs(specz)));
spec = ind22||specse||specz||pspec;
cnm = {"Effect" "se" "Z" "p"};
print "*****************************************************";
print "NORMAL THEORY TESTS FOR INDIRECT EFFECTS";
print "Indirect Effects of IV on DV through Mediators (ab paths)";
print spec [rowname = nms colname = cnm format = 9.4];
end;end;
end;
end;
if (btn > 1) then;do;
nms = {"TOTAL"}//nm[3:(nv-nc),1];
if (nv-nc-2) > 1 then do;if (&contrast = 1) then do;
crst=j((n+1+btn),((nv-nc-2)*(nv-nc-3)/2),0);
kk=1;
do ic = 2 to (nv-nc-2);
do ic2 = (ic+1) to (nv-nc-1);
crst[,kk]=indeff[,ic]-indeff[,ic2];
kk=kk+1;
end;
end;
indeff = indeff||crst;
cnam2=cname[1:(kk-1),1];
nms = nms//cnam2;
end;
end;
lvout = indeff[2:(n+1),];
tdotm = lvout[+,]/n;
tm = j(n,ncol(lvout),1)*diag(tdotm);
topa=(((n-1)/n)*(tm-lvout))##3;
topa=topa[+,];
bota =((((n-1)/n)*(tm-lvout))##2);
bota=bota[+,];
bota=6*sqrt(bota##3);
ahat = topa/bota;
indsam = indeff[1,]`;
boot = indeff[(n+2):nrow(indeff),];
mnboot = (boot[+,]/btn)`;
xt=boot-j(btn,1)*boot[:,];
cv=(xt`*xt)/btn;
se=sqrt(vecdiag(cv));
create bootstp from boot [colname='indirect'];
append from boot;
nnn = j(1,ncol(indeff),-999);
boot = nnn//boot;
do e = 1 to (ncol(indeff));
do i = 2 to (btn+1);
ix = boot[i,e];
do k = i to 2 by -1;
k2 = k;
if (boot[(k-1),e] > ix) then;
do;
boot[k,e]=boot[(k-1),e];
end;
else;
if (boot[(k-1),e] <= ix) then;
do;
goto stpit;
end;
end;
stpit:
boot[k2,e]=ix;
end;
end;
boot = boot[2:(btn+1),];
xp=j((nrow(mnboot)+2),1,0);
do i = 1 to (nrow(mnboot)+2);
if (i <= nrow(mnboot)) then;
do;
pv = (boot[,i] < indsam[i,1]);
pv = pv[+,]/btn;
end;
else;
pv = zbca[(i-nrow(mnboot)),1];
p=pv;
if (pv > 0.5) then;
do;
p = 1-pv;
end;
y5 = sqrt(-2*log(p));
xp[i,1]=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0);
if (pv <= 0.5) then;
do;
xp[i,1]=-xp[i,1];
end;
end;
bbb = nrow(mnboot);
zz = xp[1:bbb,1];
zlo = zz + ((zz+xp[(bbb+1),1])/(1-ahat`#(zz+xp[(bbb+1),1])));
zup = zz + ((zz+xp[(bbb+2),1])/(1-ahat`#(zz+xp[(bbb+2),1])));
ahat = 0;
zlobc = zz + ((zz+xp[(bbb+1),1])/(1-ahat`#(zz+xp[(bbb+1),1])));
zupbc = zz + ((zz+xp[(bbb+2),1])/(1-ahat`#(zz+xp[(bbb+2),1])));
zlo = probnorm(zlo);
zup = probnorm(zup);
zlobc = probnorm(zlobc);
zupbc = probnorm(zupbc);
blow = int(zlo*(btn+1));
bhigh = int(zup*(btn+1))+1;
blowbc = int(zlobc*(btn+1));
bhighbc = int(zupbc*(btn+1))+1;
lowbca = j(nrow(blow),1,0);
upbca = lowbca;
do i = 1 to nrow(blow);
if (blow[i,1] < 1) then;
do;
blow[i,1]=1;
end;
lowbca[i,1]=boot[blow[i,1],i];
if (bhigh[i,1] > btn) then;
do;
bhigh[i,1]=btn;
end;
upbca[i,1]=boot[bhigh[i,1],i];
end;
lowbc = j(nrow(blow),1,0);
upbc = lowbca;
do i = 1 to nrow(blowbc);
if (blowbc[i,1] < 1) then;
do;
blowbc[i,1]=1;
end;
lowbc[i,1]=boot[blowbc[i,1],i];
if (bhighbc[i,1] > btn) then;
do;
bhighbc[i,1]=btn;
end;
upbc[i,1]=boot[bhighbc[i,1],i];
end;
print "*****************************************************";
print "BOOTSTRAP RESULTS FOR INDIRECT EFFECTS";
res = indsam||mnboot||(mnboot-indsam)||se;
cn = {"Data" "Boot" "Bias" "SE"};
print "Indirect Effects of IV on DV through Mediators (ab paths)";
print res [rowname = nms colname = cn format = 9.4];
lowperc = boot[blowp,];
upperc = boot[bhighp,];
ci = lowbca||upbca;
cn = {"Lower" "Upper"};
if (&bca ^= 0) then;
do;
print "Bias Corrected and Accelerated Confidence Intervals";
print ci [rowname = nms colname = cn format = 9.4];
end;
if (&bc ^= 0) then;
do;
ci = lowbc||upbc;
print "Bias Corrected Confidence Intervals";
print ci [rowname = nms colname = cn format = 9.4];
end;
if (&percent ^= 0) then;
do;
ci = lowperc`||upperc`;
print "Percentile Confidence Intervals";
print ci [rowname = nms colname = cn format = 9.4];
end;
print "*****************************************************";
print "Level of Confidence for Confidence Intervals";
print conf;
print "Number of Bootstrap Resamples";
print btn;
end;
if (&normal = 1) then;do;if (&c = 0) then;do;prt =1;end;end;
if (btn > 999) then;do;prt = 1;end;
if ((nv-nc-2) > 1) then;do;if (&contrast = 1) then;do;
if (prt = 1) then;do;
print "*****************************************************";
print "Indirect Effect Contrast Definitions: IndEff_1 minus IndEff2";
kk=1;
prwsv = j(((nv-nc-2)*(nv-nc-3)/2),2,"XXXXXXXX");
do ic = 1 to (nv-nc-3);
do ic2 = (ic+1) to (nv-nc-2);
prwsv[kk,1]=nm[ic+2,1];
prwsv[kk,2]=nm[ic2+2,1];
kk=kk+1;
end;
end;
prwsv = cnam2||prwsv;
cn = {"Contrast" "IndEff_1" "IndEff_2"};
print prwsv [colname = cn];
end;end;end;
quit;
%mend;
/* Macro ends*/;
/*Call macro into data set*/;
data test;
seed=-1;
do i = 1 to 100;
Y=10+(.5)*rannor(1);
X=2+(0.3)*rannor(1);
/*** These are the mediators *****/;
M1=1+(0.3)*rannor(1);
M2=3+(0.4)*rannor(1);
M2=5+(0.8)*rannor(1);
M4=0+(.9)*rannor(1);
/***** These are the covariates *******/;
gender=ranbin(0,1,.5);
age=60+(5)*rannor(1);
edu=12+(1)*rannor(1);
output;
end;
run;
/*So i want to call the macro indirect and fit this model, can any one help with the last step*/
%INDIRECT [DATA = test, Y = yvar, X = xvar, M = M1 M2 M3 M4{gender age edu}]; /* Note M=Mvlist are M1, M2, M3 and M4 and covlist are age gender and edu */
{,C = {cov}(0**)}
{,BOOT = {z}(1000**)}
{,CONF = {ci}(95**)}
{,NORMAL = {t}(0**)}
{,CONTRAST = {n}(0**)}
{,PERCENT = {p}(0**)}
{,BC = {b}(1**)}
{,BCA = {d}(0)};
ERROR:
ERROR
982
983 /*So i want to call the macro indirect and fit this model, can any one help with the last
983! step*/
984 %INDIRECT [DATA = test, Y = y, X = x, M = M1 M2 M3 M4{gender age edu}]; /* Note M=Mvlist
984! are M1, M2, M3 and M4 and covlist are age gender and edu */
NOTE: IML Ready
NOTE: Line generated by the invoked macro "INDIRECT".
1 use &data;
-
Works now
%INDIRECT (DATA = test, Y = Y, X = X, M = M1 M2 M3 M4 gender age edu, C=3, CONTRAST = 1, NORMAL
= 1, BOOT = 500);
From your other thread on this topic:
%INDIRECT [DATA = test, Y = y, X = x, M = M1 M2 M3 M4{gender age edu}];
generates an error in the READ ALL because it resolves to
read all var{y x M1 M2 M3 M4{gender age edu}} into dd;
and the extra {} inside the var{ } are not acceptable syntax.
Also, did you start with a program that actually produced the desired output BEFORE writing this macro?
Works now
%INDIRECT (DATA = test, Y = Y, X = X, M = M1 M2 M3 M4 gender age edu, C=3, CONTRAST = 1, NORMAL
= 1, BOOT = 500);
Available on demand!
Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.