Proc IML Full Factorial Matrix

[Sanscrit_2prov]

Thank you so much. I've never used this forum before and it's so helpful due to people like you.  Many Thanks

[Rick_SAS]

Do you know that you can get the missing value pattern matrix from PROC MI?

"Examine patterns of missing data in SAS"

If the data matrix is not too big, you can use heat maps to visualize the missing data patterns.

[PaigeMiller]

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@Sanscrit_2prov wrote:

Unfortunately I have I can have more than 15 factors as they are combinations of covariate patterns. I did see Proc Factex and will check that out also. Thank you

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Wait a second ... full factorial with more than 15 factors? That will be huge, even if it is a 2-level design. And this is the first time you have mentioned covariates ... a full factorial with covariates, how are the covariates to be handled? Are they part of the full factorial?

Please explain this.

[Sanscrit_2prov]

We are just using the design matrix to indicate the presence or absence of binary (present/absent) predictors (or covariates). I should have been clearer that this isn't an experiment. It is a program looking at average attributable risk over different patterns of predictors. The matrix tells us which predictors are present, It is then used in further matrix operations that multiply the beta coefficients for the predictors that are present, and the resulting sum is used in further calculations.

[PaigeMiller]

The matrix tells us which predictors are present, It is then used in further matrix operations that multiply the beta coefficients for the predictors that are present

This is what PROC SCORE does. SAS has done the hard work of programming this specific type of matrix calculation, so you don't have to. They have tested it thoroughly and debugged it. 

[Rick_SAS]

I don't understand what the data look like. Could you please provide an example data set (or matrix) that has three columns and five observations, and also supply the result that you expect to get?