[R-sig-ME] three-levels of nesting in poisson mixed effect regression?

[ONKELINX, Thierry]

Dear Andrey,

Don't use dummy variables, use a factor instead.

Then your formula reduces to

Outcomes ~ offset(log(N)) + 0 + disease:(Gender  + FE1 + FE2 + FE3) +  (0 + disease|State) + (0 + disease|County)

Gender is not suitable as random effect because it has to few levels.

Best regards,

Thierry

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
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1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx op inbo.be
www.inbo.be

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-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces op r-project.org [mailto:r-sig-mixed-models-bounces op r-project.org] Namens Rzhetsky, Andrey [BSD] - MED
Verzonden: zaterdag 1 juni 2013 21:05
Aan: R-SIG-Mixed-Models op R-Project.org
Onderwerp: [R-sig-ME] three-levels of nesting in poisson mixed effect regression?

Could you please help me out with notation in lme4?

I am trying to implement a bivariate county-level outcome (Poisson response with county-level offset N) over incidence of 2 diseases, dis1 and dis2, using dummy binary indicators, dis1 and dis2, and fixed effects duplicated as dis1*fixed_eff_i and dis2*fixed_eff_i.

My data is nested at several levels: states, counties, and diseases (also genders?).  Could you please help me to check/define notation  that would reflect most faithfully the 3-level structure?

This is what I have now.

Out  <- glmer(formula = Outcomes ~ 1 + offset(log(N)) + (0 + dis1|State) + (0 + dis2|County) + (0 + dis1|State) + (0 + dis2|County) + dis1.Gender + dis2.Gender + (other fixed effects), naGQ = 7,verbose=FALSE,family=poisson,REML=FALSE,data=data,na.action = na.exclude, maxIter=200000, maxFn=10000000)")

Would be very grateful for any clarification/correction.

Thank you!

Andrey


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