[R-sig-ME] Mixed model vs GEE

[Milani Chaloupka]

One useful reference is :

Muff S, Held L, Keller L (2016) Marginal or conditional regression models for correlated non-normal data? Methods in Ecology and Evolution 7: 1514–1524. doi: 10.1111/2041-210X.12623

Milani


> On 5 Nov 2021, at 10:38 am, Ben Bolker <bbolker using gmail.com> wrote:
> 
>   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]]
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