[R-sig-ME] model specification for repeated measure

[Thierry Onkelinx]

Dear Dot,

The specification of your covariates seems reasonable to me. You need
to check if the Gaussian distribution is relevant for your
measurements on mental health.

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 op inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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2018-02-01 11:37 GMT+01:00 Dot Dumuid <haveaballphysio op gmail.com>:
> Dear mixed model experts,
> We have a dataset of older adults. We measured their mental health (MH) 6
> months before retirement and again 12 months post retirement.
> At both of these time points we also measured their physical activity (PA)
> (min/day), income (INC) and general health (GH).
> We would like to create a model that tells us if change in physical
> activity over the retirement threshold predicts change in mental health,
> and we'd like to use the model to predict how much mental health is
> predicted to change when physical activity is increased from perhaps 15
> minutes to 60 minutes. We'd like to use a mixed model rather than just
> using change (difference) scores. And we'd like to control for things like
> change in general physical health and change in income.
>
> This is what the data look like
>
> *ID  time  MH    PA    GH    INC*
> 01  pre     4      15     56     560
> 02  pre     5      30     30    1200
> ..    .....     ..       ..       ..        ...
> 01  post   7      40     50      50
> 02  post   8      45     30      0
>
> I'm not sure how best to build the model. Something like this?
>
> model <- lmer (MH ~ PA * time + GH + INC + (1|participant.ID) )
>
> Thank you in advance.
> Dot
>
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>
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