Mixed Model: Subjects v.s. Random Factor

[blastStu]

Hi,
When using SPSS to do a Linear Mixed Model it first presents a dialogue box with boxes for Subjects and Repeated Measures.

Later on, when you build your model and build the random factors SPSS lists at the bottom of the dialogue box the variables that you entered at the beginning. If you move one of these to the right hand 'Combinations' box, then the procedure adds this variable as a \SUBJECT command in the SYNTAX.

My question is this: What is the difference between adding your individuals Subject Identifier here from adding the ID as a Main Effect Random Factor (which would be \RANDOM in the syntax)?

If I don't have the \SUBJECT command, is SPSS doing anything with the variables that I entered at the very beginning of the procedure?

Many Thanks,

S.

[TheAnalysisFactor]

I've never used the dialog boxes for Mixed (for this exact reason--it's too hard to tell what the heck they're doing).

So are you basically asking about the difference between using a /Random subcommand and a /Repeated? You can have a |Subjects option in both.

They're doing totally different things, though. The Repeated statement is adjusting the residuals to take into account that they're correlated for the same Subject. (And you can choose the exact pattern of correlations by specifying the Covariance matrix).

The Random statement is actually creating a new parameter in the model to take the effect of Subject into account. In a simple one-way repeated measures model (with or without a between subjects factor), you can actually get the exact same result either way, if you specify the covariance matrices right. But if your model gets complicated, you have to be more careful.

If you describe your model more specifically (and it's not too complicated), I can try to help you specify it. This gets pretty tricky.

Karen

[blastStu]

Hi Karen,
Thanks so much for your reply.

I'm actually concerned just about the Random statement actually I think. I'm using this, as you say, to take the effect of my subject into account. However, I don't know what the difference between these two statements are:

/RANDOM=fullgroup Individual | COVTYPE(VC).

and


/RANDOM=fullgroup | SUBJECT(Individual) COVTYPE(VC).

In the first I have the individual and their group as main effects, whereas in the second the individual is listed using the SUBJECTS statement. What is different between these two?

Many Thanks,

S.

[TheAnalysisFactor]

The first one is creating a random intercept for both Fullgroup and Individual.

Since you're not specifying a subject, there must be more than one value for each fullgroup and for each individual. Or it wouldn't run.

The second one is creating a random slope for Fullgroup (and is specifically leaving out a random intercept) across Individuals.

It would be the same as saying:

/RANDOM=fullgroup*Individual| COVTYPE(VC).

In case you're not familiar with the random intercept/random slope terminology (and many people who primarily use ANOVA aren't), what this essentially means is the first is adding a parameter to the model to specifically measure the variance of the Fullgroup measures AND a parameter to measure the variance among individuals.

The second one is saying the slope of fullgroup on the DV differs across individuals, and the extra parameter is measuring how much the slope differs.

Either is a plausible model in specific situations. The first is more common, but I did just see an example of the second. It's pretty rare, though, to fit a random slope without a random intercept. (In the case I saw, the intercepts couldn't vary, because they were all, by definition, 0).

Hope that helps and doesn't confuse. It took me years to figure this stuff out.

Karen

[blastStu]

Thanks Karen, that's much appreciated.

I'm going to slowly digest your answer, but I think I get it!

S.