[R-sig-ME] Mixed model vs GEE

[Ben Bolker]

    I think that depends on what kind of questions you are asking ... ?? 
(If anyone wants to point to a great resource on marginal vs conditional 
models and when each type is appropriate, that would be great.  I know 
this distinction is discussed in Agresti's _Categorical Data Analysis_ 
book but I don't know if it goes into detail / gives examples about when 
one would want either one ...)

On 11/4/21 8:22 PM, Tahsin Ferdous wrote:
> Hi all,
> 
> 
> I am analyzing repeated measures data. Both the mixed model and generalized
> estimating equation are appropriate for my data. In this case, how can I
> decide that which one is better (LMM or GEE)? I know that GEE is a *marginal
> model*. It seeks to model a population average. Mixed-effect/Multilevel
> models are *subject-specific*, or *conditional*, models. Thanks.
> 
> 
> Best,
> 
> Tahsin
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>