You might consider using PROC GLMPOWER for the power and sample size computations for ANOVA models. Here is an example --
https://go.documentation.sas.com/doc/en/pgmsascdc/v_017/statug/statug_glmpower_examples03.htm
Thanks,
Jill
You might consider using PROC GLMPOWER for the power and sample size computations for ANOVA models. Here is an example --
https://go.documentation.sas.com/doc/en/pgmsascdc/v_017/statug/statug_glmpower_examples03.htm
Thanks,
Jill
Thanks a lot for this link. Indeed very helpful. I have a pilot study from which I would like to estimate the error standard deviation and correlation matrix. I use
```
proc corr data = ccl2_t;
var _0 _12 _24 _36 _48;
run;
```
to obtain the correlations but I get some negative values which do not suit for the proc glmpower. Do you know how that can be fixed? How can I simply enter the correlation matrix?
For the error standard deviation I simply find the SD of the mean differences. Is that a right approach?
You can enter negative correlation values in PROC GLMPOWER. The documentation below shows various ways of entering values for the MATRIX()= option --
The STDDEV= is the error standard deviation, or root MSE. You might considering fitting a PROC GLM model to a reasonable data and use the root MSE from the output.
Thanks,
Jill
If you have good measures of the residual error and the correlations, consider using the method developed by Walt Stroup, and outlined in Chapter 12 of SAS for Mixed Models, 2nd ed. The book provides an analytic method using PROC MIXED and then works through a simulation method.
SteveDenham
Hello Steve,
Any suggestions if I don't have access to SAS for Mixed Models, 2nd ed. ?
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