[R-sig-ME] novel correlation structure for nlme package, lme function

[Thierry Onkelinx]

Dear Steve,

I'd create two variables
time_treatment <- ifelse(group == "treatment", time, 0)
time_placebo <- ifelse(group != "treatment", time, 0)

And then use ~ time_treatment + time_placebo | id as random effect.

This should give you the two random slope, each with it own variance.

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

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Op do 16 jul. 2020 om 20:35 schreef Edland, Steven <sedland using health.ucsd.edu
>:

>
> Hello my programmer friends.  I am wondering if anyone has written a
> corStruct for this lme call:
>
> lme(y~time*group, random= ~time|id)
>
> In this call, the covariance structure implied by (time|id) is assumed
> constant across groups.  We would like to model these random effects
> separately in the two groups.
>
> Motivation:  In a clinical trail with an _effective_ treatment, response
> to treatment will  be variable (variance of the random slopes will be
> greater in the treatment arm).
>
>
> Thank you in advance for any thoughts where I might find such a corStruct.
>
> Steve Edland & Yu Zhao
>
>
> Sincerely,
> Steve Edland
>
> Steven D. Edland, Ph.D.
> Professor
> Dept. of Family Medicine & Public Health
> Dept. of Neurosciences
> University of California, San Diego
> 9500 Gilman Dr. M/C 0948
> La Jolla, CA 92093-0948
> http://biostat.ucsd.edu/sedland.htm
>
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>
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