novel correlation structure for nlme package, lme function

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 at 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 at 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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