R-beta: repeated measures
Peter Dalgaard BSA
p.dalgaard at biostat.ku.dk
Wed Feb 25 11:34:18 CET 1998
Jim Lindsey <jlindsey at luc.ac.be> writes:
> > Jim> R itself has nothing for repeated measures. However, I am developing a
> > Jim> complete set of four libraries that will handle most any repeated
> > Jim> measures problem, normally distributed or other. This includes two
> > Jim> functions in one of the libraries that will do the so-called anova
> > Jim> approach plus ARMA. They will do everything in my Repeated
> > Jim> Measurements book (OUP 1993) and much more.
> > Jim> I am waiting until R stabilizes a bit before releasing them but will
> > Jim> soon be asking for volunteers to aid in preliminary testing.
> > Jim> Jim
> > He was also badly missing S-plus's aov(.) function...
> > and I explained how he could use anova( lm(...) ) for FIXED effects
> > anova, and that nothing is yet available for random (or mixed) effects.
> > Martin.
> Just a warning. These things are not as simple as aov. It should still
> be implemented! Mine are general enough to do any nonlinear model for
> both mean and variance (e.g.PKPD), generalized linear mixed models,
> multivariate survival with any censoring pattern, completely
> unbalanced data, etc. Hence, with this level of generality, the
> interface is not always that simple: lists of time-varying covariates etc.
Yes. We need aov().
Also note that Bates & Pinheiro are in the process of porting lme
(linear mixed effects models) to R. From what I have seen, this does
at least what SAS PROC MIXED does, only better...
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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