Hi everyone, I am learning how to do simulations in SAS for different methods of analyzing a two-group pretest-posttest design. I simulated ANCOVA successfully (I think) -- see the code below (this code uses a truncated normal distribution). But now I want to simulate gain scores (y-x), and I am confused... In ANCOVA, I just simulated y under particular conditions, and then tested the model through proc glm. Data MC (keep = x y g sampleID);
Fa = cdf('Normal', -6, 0, 1);
Fb = cdf('Normal', 6, 0, 1);
call streaminit(12345678);
do sampleID = 1 to 1000;
do g = 0, 1;
do i = 1 to 500;
v1 = Fa + (Fb-Fa)*rand('Uniform');
v2 = Fa + (Fb-Fa)*rand('Uniform');
x = 0*g + quantile('Normal', v1, 0, 1); /* no effect of group on x */
y = 1*x + 0*g + quantile('Normal', v2, 0, 1); /* perfect stability between x and y; no effect of g on y */
output;
end;
end;
end;
run;
proc glm data = MC outstat=myStat noprint;
BY sampleID;
class g;
model y = g x / ss3;
run; But with gain scores this will not work because on the one hand gain = x-y but on the other hand I need to simulate gain to specify no effect of the group (see the attempt below...). But that's not right as I can't have gain to equal to two different expressions... Data MC (keep = x y g sampleID);
Fa = cdf('Normal', -6, 0, 1);
Fb = cdf('Normal', 6, 0, 1);
call streaminit(12345678);
do sampleID = 1 to 1000;
do g = 0, 1;
do i = 1 to 500;
v1 = Fa + (Fb-Fa)*rand('Uniform');
v2 = Fa + (Fb-Fa)*rand('Uniform');
v3 = Fa + (Fb-Fa)*rand('Uniform');
x = 0*g + quantile('Normal', v1, 0, 1); /* no effect of group on x */
y = 1*x + quantile('Normal', v2, 0, 1); /* perfect stability between x and y */
gain = y - x;
gain = 0*g + quantile('Normal', v3, 0, 1);
output;
end;
end;
end;
run;
proc glm data = MC outstat=myStat noprint;
BY sampleID;
class g;
model gain = g / ss3;
run; How to do simulations of gain scores properly? I read the book of Rick Wicklin "Simulating data with SAS" but he doesn't go into simulations of gain scores or the like... Thank you in advance for any help and/or feedback!
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