marieline gentes writes:
> Dear list,
>
> I'm just starting to learn how to use glmmPQL and I
> have a very basic question. I'm a bit embarrassed asking
> this, but I could not find a clear answer anywhere,
> and I did search quite a bit. Unfortunately there is no
> one around me to ask - none of my collegues work with glmmPQL.
>
> Here is the fixed effects section of my output:
>
> Fixed effects: cbind(ColoYes.allnoF24, ColoNo.allnoF24) ~ year.coded + sex
>
> Value Std.Error DF t-value p-value
> (Intercept) 1.4442270 0.1824173 74 7.917161 0.
> year.codedY2011 -0.1733713 0.1864744 74 -0.929732 0.3555
> year.codedY2012 -0.3004284 0.2027411 74 -1.481833 0.1426
> sexM 0.4403108 0.1507471 74 2.920857 0.0046
> I simply want to report the fact that year (categorical, three
> levels) is not significant. In traditional linear models I would
> simply report the p value for treatment "year" from an anova
> table. But my understanding is that producing an anova
> from glmmPQL is not possible (?). Reporting those individual p
> values of my three years separately seems clumsy and out of place...
> What is the proper way to do this ?
Since glmmPQL doesn't technically compute likelihoods, and its
authors are purists, it doesn't provide standard likelihood-based
model comparison tools.
You could switch to glmer, from the lme4 package, or I suppose
you could use Fisher's method or some equivalent to combine the
p values: see this thread (which also suggests alternatives)
http://r.789695.n4.nabble.com/combining-P-values-using-Fisher-s-method-
td832459.html [URL broken]
or
http://finzi.psych.upenn.edu/R/library/MADAM/html/fisher.method.html
good luck
Ben Bolker
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