Hello,
I am struggling to understand how denominator degrees of freedom and
subsequent significance testing based upon them works in nlme models.
I have a data set of 736 measurements (weight), taken within 3
different age groups, on 497 individuals who fall into two
morphological catagories (horn types).
My model is: Y ~ weight + horn type / age group, random=~1|individual
I am modeling this using glmm.PQL function with family=neg.bin
(negative binomial distribution, estimating theta based upon a glm
without individual as a random effect). My data set will not be
balanced, with varying numbers of measurements taken on different
individuals and some individuals have no weight measures just a
morphological type.
My output:
denDF numberdf
Intercept 495
weight 232 1
horn type 495 1
horn type:age 232 4
So my question is where do these denDF come from and how are they
calculated? I wish to then test significane of these fixed effects and
can get F-ratio's and P-values but are these appropriate?
Thank-you for your time.
Kind regards
Matthew
*********************************
Matt Robinson
Institute of Evolutionary Biology
Room 413, Ashworth Labs,
King's Buildings,
University of Edinburgh
EH9 3JT, UK
Tel: 0131 650 5990
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