Hi,
I need to analyze the influences of several factors on a variable that is a
measure of fecundity, consisting of 73 observations ranging from 0 to 5. The
variable is continuous and highly positive skewed, none of the typical
transformations was able to normalize the data. Thus, I was thinking
Thanks for your responses.
I knew that when you include an interaction term in a model you must include
the main effects of each of the factors. Therefore, I assumed that SAS will
do that by default. In most statistical packages, as in R, the main effects
are automatically added when you include
Sorry, I realized that somehow the message got truncated. Here is the
remaining part of the SAS output:
Solutions for Fixed Effects:
Effect DIST DW ELI SEX SEAS Estimate Std. Error
DF t Value Pr > |t|
Intercept
ained with R and SAS.
Thanks,
Andrea Previtali
Post-doc fellow
Dept. of Biology,
Univ. of Utah.
lmer output:
Generalized linear mixed model fit using PQL
Formula: SURV ~ SEX * ELI + DW * DIST + SEAS + DEN + WT + (1 | SITE)
Family: binomial(logit link)
AIC BIC logLik deviance
1539 1606 -75
~pig.time|pig.id,data=pigs)
I have added the package "nlme" and to confirm that it was installed correctly
I requested the list of functions included in the package (library(help=nlme))
and I do see groupData in the list.
I am using R 2.6.1 in Windows XP.
I'll appreciate your hel
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