topic Re: Proc mixed : repeated in Statistical Procedures

Proc mixed : repeated

Susana0000 — Wed, 26 May 2021 23:13:22 GMT

Hello

I am a new SAS user and have come across proc mixed.

I was wondering why sometimes no variable is specified in the repeated statement and other times it is.

When no variable is specified, what does SAS assume?

Re: Proc mixed : repeated

gcjfernandez — Thu, 27 May 2021 06:06:37 GMT

Proc Mixed Repeated statement documentation: https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.3/statug/statug_mixed_syntax14.htm

differentiates the following:

For many repeated measures models, no repeated effect is required in the REPEATED statement. Simply use the SUBJECT= option to define the blocks of R and the TYPE= option to define their covariance structure.

In this case, the repeated measures data must be similarly ordered for each subject, and you must indicate all missing response variables with periods in the input data set unless they all fall at the end of a subject’s repeated response profile.

These requirements are necessary in order to inform PROC MIXED of the proper location of the observed repeated responses.

Specifying a repeated effect is useful when you do not want to indicate missing values with periods in the input data set.

The repeated effect must contain only classification variables.

Make sure that the levels of the repeated effect are different for each observation within a subject; otherwise, PROC MIXED constructs identical rows in corresponding to the observations with the same level.

This results in a singular R and an infinite likelihood.

Whether you specify a REPEATED effect or not, the rows of R for each subject are constructed in the order in which they appear in the input data set.

Re: Proc mixed : repeated

jiltao — Thu, 27 May 2021 13:26:01 GMT

@gcjfernandez answered your question very well. Thanks!

I just want to point out that although it is not necessary to specify the repeated effect in the REPEATED statement in PROC MIXED, it is highly recommended to include the repeated effect. In the case of unbalanced repeated measures data / missing repeated time points, omitting the repeated effect might result in calculations not what you intended for certain models.