[R-sig-ME] GLS with small-sample-sizes corrections

j@z@vr@kidis m@ili@g off @ki@@l j@z@vr@kidis m@ili@g off @ki@@l
Wed Oct 10 12:45:47 CEST 2018

Dear all,

My question is more theoretical I guess and less practical. Is it possible/necessary/appropriate to apply small-sample-size corrections, such as Satterthwaite and Kenward-Roger approximation, in a marginal model via GLS ? So no random parts, but only covariance structure... I am working with datasets of 5-10 observations per group. I already use the REML instead of the conventional ML, but I was wondering if this is not enough. Although a quick check I did, gave small to none differences between with and without these corrections... 

And of course, if the answer is "yes, you should apply them", can you tell me if and how can I do it in R with lme4/nlme ? I currently use the nlme::gls() function...

Kind regards,

John Zavrakidis

Junior Researcher - Statistician
Department of Epidemiology and Biostatistics

e-mail:  j.zavrakidis using nki.nl

The Netherlands Cancer Institute | Plesmanlaan 121 | 1066 CX AMSTERDAM | www.nki.nl

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