[R-sig-ME] lme4 for a 4 level hierarchy

[Thierry Onkelinx]

Dear Kim,

Since every nurse has a single binary response, you can summarise the data
at the ward level
c(number of nurse success, number of nurses failure)
In this case the ward random effect would be an observation level random
effect. I'm not sure if you want that.

Best wishes,

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
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Op wo 4 sep 2024 om 13:55 schreef Kim Pearce via R-sig-mixed-models <
r-sig-mixed-models using r-project.org>:

>
> Hello everyone,
>
> If I may, I'd like to ask if I am visualising the correct syntax to use
> for a hypothetical situation using a mixed effects logistic regression with
> a 4 level hierarchy.
>
> Say we have nurses which are nested within wards and the wards are nested
> within hospitals and hospitals are nested within regions of the UK. Each
> nurse has a binary response recorded (Y). Nurses are at level 1, wards at
> level 2, hospitals at level 3 and regions at level 4.  Say each ward has
> one category of an ordered 3 category intervention applied where a higher
> ordered category of intervention was hypothesised to affect a nurse's
> binary response.
>
> Hypothetically, I wish to generate a model with a fixed effect for
> "Intervention" and random (and fixed) intercepts for (i) each region, (ii)
> each region x hospital combination and (iii) each region x hospital x ward
> combination.  Would the following syntax be appropriate?
>
> Note intervention appears in the model as a factor below.
>
>
> m1<-glmer(Y~interventionf+(1|region/hospital/ward),data=data,family=binomial,control=glmerControl(optimizer="bobyqa"))
>
> Many thanks for your views.
> Kind regards,
> Kim
>
> Dr Kim Pearce PhD, CStat, Fellow HEA
> Newcastle University
>
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