Displaying 9 results from an estimated 9 matches for "pdclasses".
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2010 Apr 14
3
pdMat
Alguien tiene experiencia en escribir una pdMat. Para aquellos que no lo
recuerden son las matrices de covarianzas de los efectos aleatorios que
ajusta la función lme de la librería nlme
Estas matrices tiene especial importancia en aplicaciones de genética de
poblaciones y en particular en mapeo de asociación. Pinheiro y Bates dicen
que el usuario puede crear sus propias pdMat y sugiere como
2006 Mar 22
1
An lme model that works in old R.2.1.1 but not always in R.2.2.0 - why?
Following lme model runs fine in general under R.2.1.1 but only for 9 out
of my 11 response variables under R.2.2.0.
model for one of my response variables:
lme(Yresp~F1fix,random=list(const=pdBlocked(list(~F2mix-1,~Ass:F1fix-1,~F3mix-1,~F1fix:F3mix-1,~F2mix:F3mix-1),pdClass="pdIdent")))
Yresp is my response variable, F1fix is a fixed effect factor whereas
F2mix and F3mix are random
2013 Oct 26
2
Problems with lme random slope+intercept model
Dear all,
I'm trying to fit a model on ecological data in which I have measured a few
biotic and abiotic factors over the course of a few days in several
individuals. Specifically, I'm interested in modelling y ~ x1, with x2, x3,
and 'factor' as independent variables. Because data suggests both slope and
intercept (for y ~x1) might differ between individuals, I'd want to
2006 Jun 30
1
lme and SAS Proc mixed
I am trying to use lme to fit a mixed effects model to get the same
results as when using the following SAS code:
proc mixed;
class refseqid probeid probeno end;
model expression=end logpgc / ddfm=satterth;
random probeno probeid / subject=refseqid type=cs;
lsmeans end / diff cl; run;
There are 3 genes (refseqid) which is the large grouping factor, with
2 probeids nested within each refseqid,
2011 Aug 08
1
mixed model fitting between R and SAS
Hi al,
I have a dataset (see attached), which basically involves 4 treatments for a chemotherapy drug. Samples were taken from 2 biopsy locations, and biopsy were taken at 2 time points. So each subject has 4 data points (from 2 biopsy locations and 2 time points). The objective is to study treatment difference.?
I used lme to fit a mixed model that uses "biopsy.site nested within pid"
2003 Dec 24
0
Solution to "Can anyone help me reproduce this SAS Mixed output??"
To those who might be interested -- following is the solution to my
previous post regarding reproducing output from SAS Proc Mixed for a
two-factor crossed random effects ANOVA model.
I am graciously endebted to the kind replys from two statisticians for
this solution whose names I will refrain from mentioning for the sake of
privacy.
I hope this helps someone?!
-- Phil Turk
> hw7 <-
2006 Jun 30
0
SAS Proc Mixed and lme
I am trying to use lme to fit a mixed effects model to get the same
results as when using the following SAS code:
proc mixed;
class refseqid probeid probeno end;
model expression=end logpgc / ddfm=satterth;
random probeno probeid / subject=refseqid type=cs;
lsmeans end / diff cl; run;
There are 3 genes (refseqid) which is the large grouping factor, with
2 probeids nested within each refseqid,
2012 Jun 21
1
lme random effects in additive models with interaction
Hello,
I work with a mixed model with 4 predictor variables Time, Size, Charge,
Density and Size, Charge, Density are factors, all with two levels. Hence I
want to put their interactions with Time into the model. But, I have two
data sets (Replication 1 and 2) and I want that Replication is random
effect. Here is my code:
knots <- default.knots(Time)
z <- outer(Time, knots, "-")
2010 Feb 04
1
random slope models with lme --> failured to converge
Dear all,
I am working on a data set in which I have sequentially measured egg
temperatures ("eggtemp") in birds incubating in different ambient
temperatures ("treat", sample data set below), "id" is not replicated within
treatment.
id treat eggtemp
1 79 3 30.90166
2 42 3 34.94044
3 10 3 32.69945
4 206 3 36.64127
5 23 3 31.80055
6