To whom it may concern:
I am using lmer for a statistical model that includes non-normally
distributed data and random effects. I used this same function in the
most recent version of R as of fall 2005, and have re-done some of the
same analyses using all of the same files, but with the newest version
of R (2.2.1). I get answers that are not exactly the same (although I
do get the same general patterns of significance). Is there any reason
why an updated version of lmer in R would give different answers than
the same function in a previous version? See example below.
I appreciate your help. Please direct answers to [EMAIL PROTECTED]
Sincerely,
Tracy S. Feldman
Postdoc, The Samuel Roberts Noble Foundation
Example:
The model formulas (same in both):
fitvisit1.1<-lmer(visitsR~dist + ctrt + (1|rep) + (1|field), family =
poisson, method = "ML")
fitvisit1.3<-lmer(visitsR~dist + (1|rep) + (1|field), family = poisson,
method = "ML")
Done in fall 2005 (I forget the most recent version then):
> anova(fitvisit1.1, fitvisit1.3, test = "Chisq")
Data:
Models:
fitvisit1.3: visitsR ~ dist + (1 | rep) + (1 | field)
fitvisit1.1: visitsR ~ dist + ctrt + (1 | rep) + (1 | field)
Df AIC BIC logLik Chisq Chi Df Pr(>Chisq)
fitvisit1.3 7 855.11 878.74 -420.56
fitvisit1.1 8 856.63 883.63 -420.31 0.4856 1 0.4859
Done in Feb 2006 (in R 2.2.1):
> anova(fitvisit1.1, fitvisit1.3, test = "Chisq")
Data:
Models:
fitvisit1.3: visitsR ~ dist + (1 | rep) + (1 | field)
fitvisit1.1: visitsR ~ dist + ctrt + (1 | rep) + (1 | field)
Df AIC BIC logLik Chisq Chi Df Pr(>Chisq)
fitvisit1.3 6 875.04 895.29 -431.52
fitvisit1.1 7 876.69 900.32 -431.35 0.3487 1 0.5549
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