My design involves three dependent variables. They are count data: frequencies of certain words used in a 20-min conversation. They're also repeated measure: the same subjects engaged in three 20-min conversations on three different topics and the use of certain words were counted alongside other variables. There is a factor of 2 levels and a covariate (IQ). My sample size is small (25) and there is an unequal number of subjects between the levels (13 and 12).

I've done a ton of online search and gone through a dozen of stats books but didn't find an appropriate model (I probably have missed something in my search). I think I am looking for a mixed design ANCOVA for count data (mixed effects negative binomial regression perhaps?). Any suggestions?

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#### Best Answer

This sounds like a repeated measures version of shared frailty models. From what you, say, mixed effects negative binomial or mixed effects Poisson models sound like they would be very reasonable. I.e. you would at a minimum have a random subject effect, a random outcome effect (for the type of thing you are measuring) that would not yet reflect whether two records are from the same conversation, which you could do by numbering conversations across subjects and adding a random conversation effect. To use the notation of the `lme4`

R package: `glmer(count ~ (1|subject)+(1|outcome)+(1|conversation) + factor(something) + IQ, family=poisson(link = "log"))`

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