[R-sig-ME] problem with lme4 glmer
Thierry Onkelinx
th|erry@onke||nx @end|ng |rom |nbo@be
Tue Oct 20 10:29:29 CEST 2020
Dear Mark,
Please keep the mailing list in cc. There are a dozen R packages that fit
GEE models. Have a look at
https://cran.r-project.org/web/packages/available_packages_by_name.html and
search for GEE. I've used geepack in the past. Other packages might be more
suitable for your needs.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be
///////////////////////////////////////////////////////////////////////////////////////////
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
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Op ma 19 okt. 2020 om 20:04 schreef Hauber, Mark Erno <mhauber using illinois.edu
>:
> Thanks Thierry, for the quick respond.
>
> Is there a GEE equivalent in R, please? I work with Justin and I keep
> finding glmer as the solution which is not what we are after.
>
> Thanks,
>
> Best, Mark
> _______________________________
> Mark E. Hauber, Ph.D., D.Sc. (he/him)
> Harley Jones Van Cleave Professor of Host-Parasite Interactions
>
> Department of Evolution, Ecology, and Behavior;
> School of Integrative Biology;
> University of Illinois at Urbana-Champaign,
> 469 Morrill Hall, 505 S. Goodwin Avenue, Urbana, IL 61801, USA
> www.cowbirdlab.org @cowbirdlab
>
>
> ________________________________________
> From: Thierry Onkelinx <thierry.onkelinx using inbo.be>
> Sent: Monday, October 19, 2020 12:58 PM
> To: Rhodes, Justin S
> Cc: r-sig-mixed-models using r-project.org; Hauber, Mark Erno
> Subject: Re: [R-sig-ME] problem with lme4 glmer
>
> Dear Justin,
>
> First of all you are comparing two different algorithms: GEE vs mixed
> models. GEE estimates 'population average' estimates for the fixed effect.
> The mixed models fixed effect refers to an average individual. Those will
> be by definition different.
>
> Very large estimates and standard errors indicate (quasi) complete
> separation, leading to numerical instability. Rather a problem with the
> data / model formulation than with the algorithm.
>
> Best regards,
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be<mailto:thierry.onkelinx using inbo.be>
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be<http://www.inbo.be>
>
>
> ///////////////////////////////////////////////////////////////////////////////////////////
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
> ///////////////////////////////////////////////////////////////////////////////////////////
>
> [
> https://inbo-website-prd-532750756126.s3-eu-west-1.amazonaws.com/inbologoleeuw_nl.png
> ]<https://www.inbo.be>
>
>
> Op ma 19 okt. 2020 om 19:46 schreef Rhodes, Justin S <jrhodes using illinois.edu
> <mailto:jrhodes using illinois.edu>>:
> Dear R project mixed models users:
>
> We used "lmer4", "glmer" function see below. I attached the data set.
> The programs and results for SAS and R are shown below. Results are
> incredibly different, and seem impossible to explain by differences in
> computational algorithms. The estimates from SAS are reasonable, but the
> estimates from R are clearly wrong, based on looking at the simple data.
> We realize that we are underpowered to estimate the random effect here, but
> it still should give reasonable estimates if it converges, right? Can
> someone please help us figure this out? Thanks very much for any
> information
>
> R code:
>
> #import data
> Pole<-read.table("Pole.txt",header = TRUE)
>
> #define factors
> Pole$Color<-as.factor(Pole$Color)
> Pole$Treatment<-as.factor(Pole$Treatment)
> Pole$ID<-as.factor(Pole$ID)
>
> #model statement
> fm1<-glmer(Outcome ~ Eggs + Color + Treatment + (1|ID), family=binomial,
> data=Pole)
>
> #results
> summary(fm1)
>
> Estimate Std.
> Error z value Pr(>|z|)
> (Intercept) -23.4673 12.4832
> -1.880 0.06012 .
> Eggs -0.0496 3.4036
> -0.015 0.98837
> Colorspotted 36.0295 8.4055
> 4.286 1.82e-05 ***
> Treatmentsharp 12.4964 4.1453
> 3.015 0.00257 **
> ---
>
>
> SAS code:
>
> proc genmod data=temp.Pole;
> class ID Treatment Color;
> model Outcome= Eggs Color Treatment/d=bin link=logit;
> repeated subject=ID/type=cs;
> run;
>
> Analysis Of GEE Parameter Estimates
> Empirical Standard Error Estimates
> Parameter
>
> Estimate
> Standard
> Error
> 95% Confidence Limits
> Z
> Pr > |Z|
> Intercept
>
> -1.0491
> 1.3990
> -3.7911
> 1.6928
> -0.75
> 0.4533
> Eggs
>
> -0.1071
> 0.4632
> -1.0151
> 0.8008
> -0.23
> 0.8171
> Color
> blue
> 1.5046
> 0.8476
> -0.1567
> 3.1660
> 1.78
> 0.0759
> Color
> spot
> 0.0000
> 0.0000
> 0.0000
> 0.0000
> .
> .
> Treatment
> blunt
> 0.3908
> 0.2841
> -0.1660
> 0.9476
> 1.38
> 0.1690
> Treatment
> sharp
> 0.0000
> 0.0000
> 0.0000
> 0.0000
> .
> .
>
>
>
>
> Thanks very much for your help!!
>
> Justin Rhodes
> Professor
> Department of Psychology
> Beckman Institute
>
> 405 N Mathews Ave
> Urbana, IL 61801
>
> Affiliations: Neuroscience Program, Program for Ecology, Evolution and
> Conservation Biology, Institute for Genomic Biology, Division of
> Nutritional Sciences
>
> Email: jrhodes using illinois.edu<mailto:jrhodes using illinois.edu><mailto:
> jrhodes using illinois.edu<mailto:jrhodes using illinois.edu>>
> Phone: 217-265-0021
>
> Website: http://rhodeslab.beckman.illinois.edu/
>
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