Re: ANOVA, GLM and missing values
- From: Bruce Weaver <bweaver@xxxxxxxxxxxx>
- Date: Mon, 08 Aug 2005 07:27:43 -0400
Andy Spragg wrote:
In the software implementations of ANOVA that I have seen, missing values are not allowed. To analyse ANOVA-type data with missing values I have to use GLM, which ANOVA reduces to under certain circumstances.
Having now read a little about GLM, I am unable to see why it should allow missing values when ANOVA apparently does not. As far as I can see, the generalization from ANOVA lies in the conceot of a link function, and allowing this to be something other than the identity function ushers in a new dimension of modelling possibilities. However, when the link function is the identity function, GLM is supposed to reduce back to ANOVA ...
So I fail to see what else GLM brings to the party which allows missing values to be tolerated. I'd be grateful for any insights.
Most standard implementations of repeated measures ANOVA require one case (i.e., row of data) per subject, and the entire case is dropped if any of the repeated measures are missing. Is *that* what you're talking about? In cases like that, you can restructure the data to have one row per observation (so multiple rows per subject), include subject explcitily as a factor, and cajole your software into doing a repeated measures ANOVA using the between-Ss procedure (or GLM).
I would not say that missing values are "tolerated", because they are still dropped. The difference is that only the observations that are missing are dropped, not the entire subject. In SPSS, the loss of balance can result in some changes to the error terms (i.e., the MS may be the linear combination of the usual MS plus one or more others).
-- Bruce Weaver bweaver@xxxxxxxxxxxx www.angelfire.com/wv/bwhomedir .
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