Dear Han,
> I am using nlme for data from nested design. That is, "tows" are nested
> within "trip", "trips" nested within "vessel", and "vessels" nested
> within "season". I also have several covariates, say "tow_time",
> "latitude" and "depth"
> My model is
> y = season + tow_time + latitude + depth + vessel(season) +
> trip(season, vessel) + e
> In SAS, the program would be
> proc mixed NOCLPRINT NOITPRINT data=obtwl.x;
> class vessel trip tow season depth;
> model y = season depth latitude /solution; <----------fixed effects
> random vessel(season) trip(season vessel);
> run;
> My question is: How this nested mixed-effects model can be
> fitted in R-> "nlme"?
I do not know about SAS but I would guess that your model should be fitted
as something like:
lme (fixed= y ~ season + tow_time + latitude + depth,
random= ~ 1 | season/vessel/trip)
Maybe you should do some reading in the book by Pinheiro & Bates?
They explain well how to set up models.
Regards, Lorenz
-
Lorenz Gygax, Dr. sc. nat.
Tel: +41 (0)52 368 33 84 / [EMAIL PROTECTED]
Tag der offenen T�r, 11./12. Juni 2004: http://www.fat.ch/2004
Center for proper housing of ruminants and pigs
Swiss Veterinary Office
agroscope FAT T�nikon, CH-8356 Ettenhausen / Switzerland
Fax : +41 (0)52 365 11 90 / Tel: +41 (0)52 368 31 31
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