[R-sig-ME] nested mixed effects logistic regression binomial glm) results differ by function.

[Lize van der Merwe]

Thankyou, Malcolm

This is embarrassing.  You are right, the parentheses are necessary and are in the models I ran.  I am sure I typed those parentheses, but they are not in my request any more …  I think I know what happened.

Sorry about that. 

I am working through the other people’s suggestions, thankyou too.

Regards

Lize

 

 

From: Malcolm Fairbrother [mailto:M.Fairbrother at bristol.ac.uk] 
Sent: 24 April 2015 12:08
To: lizestats at gmail.com
Cc: r-sig-mixed-models
Subject: Re: nested mixed effects logistic regression binomial glm) results differ by function.

 

Dear Lize,

 

Does it make any difference if you try:

glmer(CC ~ predictor + (1 | area / household), family = binomial)

 ?

 

I may be wrong, but I thought the parentheses were important here.

 

 

Best wishes,
Malcolm

 

 

 

Date: Thu, 23 Apr 2015 18:16:26 +0200
From: Lize van der Merwe <lizestats at gmail.com>
To: <r-sig-mixed-models at r-project.org>
Subject: [R-sig-ME] nested mixed effects logistic regression binomial
        glm)    results differ by function.

Please advise:

I have a dichotomous outcome on 2500 individuals. From 18 geographical
areas, and many households nested within areas. I need to assess the
association between various predictors and my outcome, adjusting for the
correlation within households, as well as within areas. The following R
functions provide dramatically different results.

glmer(CC~predictor+1|area/household,family=binomial)

and

glmmPQL(CC~predictor, random=~1|area/household),family=binomial)

Why? Which is correct?

Thanks in advance.  (I posted this on another site too.)

Lize


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