[R-sig-ME] Partial effects in mixed models

[v_coudrain at voila.fr]

Thank you. My concern was that the model with both variables within may not be optimal because both variables are correlated and I would like to know if the 
second variable has a "pure" effect on the response variable that is independent from the effect of the first variable. Since I have a generalized mixed model with 
poisson distribution, the statistics are based on Chi test and not F tests and I think that these tests are not sequential like in anova. Am I correct? 

Best


> Message du 01/03/13 à 03h23
> De : "Steven J. Pierce" 

> A : v_coudrain at voila.fr, r-sig-mixed-models at r-project.org
> Copie à : 
> Objet : RE: [R-sig-ME] Partial effects in mixed models
> 
> Why not just run a model with both predictors instead? See King (1986) for one perspective on why extracting the residuals to use as the dependent variable in 
another model is sub-optimal. That paper is about plain old OLS regression, but I suspect it still is applicable logic. 
> 
> King, G. (1986). How not to lie with statistics: Avoiding common mistakes in quantitative political science. American Journal of Political Science, 30(3), 666-687.
> 
> 
> Steven J. Pierce, Ph.D. 
> Associate Director 
> Center for Statistical Training & Consulting (CSTAT) 
> Michigan State University 
> E-mail: pierces1 at msu.edu 
> Web: http://www.cstat.msu.edu 
> 
> 
> -----Original Message-----
> From: v_coudrain at voila.fr [mailto:v_coudrain at voila.fr] 
> Sent: Thursday, February 28, 2013 11:25 AM
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Partial effects in mixed models
> 
> Dear all,
> 
> I would like to test the effect of an explanatory variable after removing the effect of another one. I thought about calculating the model with the first explanatory 
> variable only, then take the model residuals and use the residuals as response variable to test the effect of the second explanatory variable. However, I do not 
> know if this is possible for a model containing random effects. Maybe it doesn't make sense anyway, but if it is possible, should I include the random effects in 
the 
> second model (residuals as response variable) or not, since variance explained by random effects should also have been accounted for in the first model?
> 
> Thank you for your help
> 
> Valérie
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