Regarding my original post below, THANKS to Joel Dubin, John Maindonald,
Regula Schwager-Suter, Renaud Lancelot, and Prof Brian Ripley for your most
helpful and prompt responses.
Most of my respondents cited the capacity of mixed-effect models to handle
unbalanced designs (including designs where individuals are not all measured
at the same times, or at the same no. of times) as a major advantage.
Many also provided me with the following citations:-
Diggle P.J., Liang K.-Y., Zeger S.L., 1994. Analysis of longitudinal
data. 1st ed. Oxford Statistical Science Series, ed. A.C. Atkinson, et
al. Oxford (Great Britain): Clarendon Press. 253 p.
Laird N.M., Ware J.H., 1982. Random-effects models for longitudinal
data. Biometrics, 38 : 963-974.
and I was also provided with the following helpful reference:-
Littell, R.C., Henry, P.R. and Ammermann, C.B. 1998. Statistical analysis
of repeated measures data using SAS procedures. Journal of Animal Science
76: 1216-1231.
I must say, I've never encountered another newsgroup that works nearly so
well as a newsgroup!
Duncan
-----Original Message-----
From: owner-s-news@wubios.wustl.edu
[mailto:owner-s-news@wubios.wustl.edu] On Behalf Of Duncan Mackay
Sent: Tuesday, 15 June 1999 12:10
To: S-News
Subject: [S] lme, nlme and repeated measures ANOVA
Hi Splussers,
would someone please point me at some references (or to their own opinions!)
as to the circumstances, kinds of data etc, under which one would likely
prefer to run a linear mixed-effects model (as in lme) as opposed to a
traditional univariate or multivariate repeated-measures ANOVA. And vice
versa - under what cirumstances would you likely prefer a traditional
repeated-measures ANOVA to running lme??
Many thanks,
Duncan
(.....Hope this isn't going to be one of those "If you need to ask the
question, you won't appreciate/ understand the answer" kind of days.......)
****************************************************************
Dr. Duncan Mackay
Biological Sciences
Flinders University
GPO Box 2100
Adelaide
S.A. 5001
AUSTRALIA
Phone (08) 8201 2627
FAX (08) 8201 3015
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