Help with Proc IML Simulation Error

[MetinBulus]

I am trying to simulate many samples from a multinomial logistics regression. At the moment I am keeping the number of repetations small for diagnostics purposes. I have inserted comments as much as possible to make it readable. The code aims to use a do loop within IML to generate many samples. It is expected to output two datafiles; one for simulated data and the other for parameters. Although it is not known what other errors I might have, at this stage I can't seem to be solving the problem with the following error:

ERROR: Number of columns in TempSimData does not match with the number of variables in the data set.

Please help.

option symbolgen;
** define parameters;
%let N = 600;   ** total obs;
%let NumSamples = 10;
%let beta01 = 0;
%let beta02 = log(6/4);
%let beta03 = &beta01 - &beta02;
%let beta11 = log(3);   *relationship of covariate X with T=1;
%let beta12 = log(4); *relationship of covariate X with T=2;
%let beta13 = &beta11 - &beta12;  *relationship of covariate X with T=3;
%let alpha0 = 0;   ** intercept, T=3 effect;
%let alpha1 = 0.2;   ** T=1 effect;
%let alpha2 = 0.4;   ** T=2 effect;
%let alphaX = 0.2;   ** X effect;

** simulate data;
proc iml;  
	** assign variable names and allocate space for the data and parameters;
    varNamesData={SampleID x t t1 t2 t3 y};
    varNamesParms={SampleID N PN1 PN2 PN3 beta01 beta02 beta03 beta11 beta12 beta13 alpha0 alpha1 alpha2 alphaX varY};
   	TempSimData = J(&N, NCOL(varNamesData)); 
   	TempSimParms = J(1, NCOL(varNamesParms));
    create SimData from TempSimData[c=varNamesData];
    create SimParms from TempSimParms[c=varNamesParms];
	
	** simulation loop;
	do SampleID = 1 to &NumSamples;
	  	call RANDSEED(0);
	  	** allocate space and generate x;
	  	x = J(&N, 1);	
	  	call RANDGEN(x, "NORMAL", 1, 1);
		** define linear equations;
		eta13 = &beta01 + &beta11 * x;	*T=1 vs T=3;
	  	eta23 = &beta02 + &beta12 * x;	*T=2 vs T=3;
	    ** find actual probabilities for subjects to be in each treatment level;
	    pi1 = exp(eta13) / (1 + exp(eta13) + exp(eta23));	
	    pi2 = exp(eta23) / (1 + exp(eta13) + exp(eta23));	
	    pi3 = 1 / (1 + exp(eta13) + exp(eta23));	
	  	** allocate space for treatment and actual probabilities in matrix form;
	  	t = J(&N, 1); 	
	  	p = J(&N, 3);	
	  	** fill the probability matrix from pi1, pi2, and pi3;
	  	p[,1] = pi1;	
	  	p[,2] = pi2;	
	  	p[,3] = pi3;	
	  	** generate treatment levels;
	    call RANDGEN(t , "TABLE", p);	
	    ** create dummy variables for treatment levels;
	    t1 = J(&N, 1, 0);	
	    t2 = J(&N, 1, 0);
	    t3 = J(&N, 1, 0);
	    idx1 = LOC(t=1);
		t1[idx1]=1; 
		idx2 = LOC(t=2);
		t2[idx2]=1; 
		idx3 = LOC(t=3);
		t3[idx3]=1;
		** allocate space for outcome and residuals;
	  	y = J(&N,1);	
	  	epsilon = J(&N, 1);	
	  	** generate residuals such that variance of y will approximately be 1;
	  	SigmaEpsilon = SQRT(1-sum(cov(&alpha1*t1||&alpha2*t2||&alphaX*x)));	
	  	epsilon = RANDFUN(&N, "NORMAL", 0, SigmaEpsilon);
	  	** generate y;
	    y = &alpha0 + &alpha1*t1 + &alpha2*t2 + &alphaX*x + epsilon;
	    
	    ** create a temporary simulated data for each simulation loop;
	    TempSimData = J(&N, NCOL(varNamesData));
	    TempSimData[,1] = SampleID;
		TempSimData[,2] = x;
		TempSimData[,3] = t;
		TempSimData[,4] = t1;
		TempSimData[,5]	= t2;
		TempSimData[,6] = t3;
	  	TempSimData[,7] = y;
	   	append from TempSimData;
	    
	    ** define additional parameters;
		idxN1 = LOC(t=1);
		N1 = COUNTN(t[idxN1]);
		idxN2 = LOC(t=2);
		N2 = COUNTN(t[idxN2]);
		idxN3 = LOC(t=3);
		N3 = COUNTN(t[idxN3]);
		VarY = VAR(y);
		PN1 = N1/&N;
		PN2 = N2/&N;
		PN3 = N3/&N;
		
		** save temporary parameters for each simulation loop;
		TempSimParms = J(1, NCOL(varNamesParms));
		TempSimParms[,1] = SampleID;
		TempSimParms[,2] = &N;
		TempSimParms[,3] = PN1;
		TempSimParms[,4] = PN2;
		TempSimParms[,5] = PN3;
		TempSimParms[,6] = &beta01;
		TempSimParms[,7] = &beta02;
		TempSimParms[,8] = &beta03;
		TempSimParms[,9] = &beta11;
		TempSimParms[,10] = &beta12;
		TempSimParms[,11] = &beta13;
		TempSimParms[,12] = &alpha0;
		TempSimParms[,13] = &alpha1;
		TempSimParms[,14] = &alpha2;
		TempSimParms[,15] = &alphaX;
		TempSimParms[,16] = varY;
	   	append from TempSimParms; 
	end;
	  close SimData;
	  close SimParms;
quit;

[Rick_SAS · Accepted solution]

When you are writing to two different data set, you need to use the SETOUT statement tell IML which one to write to. See the last paragraph of this article on reading/writing data in SAS/IML

...
   setout SimData;
   append from TempSimData;
...	   
   setout SimParms;
   append from TempSimParms; 

[MetinBulus]

Thanks Rick, it worked!