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Differences in degrees of freedom between a mixed-effects model and a gls model using nlme

Ben Bolker · 2015-02-09T04:36:11Z

Ken Beath writes: > > All 3 (paired t-test, mixed effect and gls with compound symmetry) are > fitting the same model, and so should give the same result. That is what > you see with the first example. The gls model is not getting it wrong > except for the df. > > For the second the 3 model results should again be the same. I'm not > certain why but it may be numerical. Even though the data come > from a model > that isn't correct for the fitting that should be irrelevant,

Ben Bolker

Sun, Feb 8, 2015 8:36 PM

Ken Beath <ken.beath at ...> writes:

For what it's worth you can easily see what gls() is doing to
get its df, and confirm that it's naive, by printing nlme:::summary.gls:

  tTable[, "p-value"] <- 2 * pt(-abs(tTable[, "t-value"]), 
        dims$N - dims$p)

For what it's worth, I've found that the df calculations used by
lme() often fail quite badly for random-slopes models ... it's often
really hard to guess, even for simpler designs (i.e. where there
really is a precise correspondence with an F distribution -- no correlation
structures or lack of balance or crossed random effects).

Thread (3 messages)

Hufthammer, Karl Ove Differences in degrees of freedom between a mixed-effects model and a gls model using nlme Feb 6 Ken Beath Differences in degrees of freedom between a mixed-effects model and a gls model using nlme Feb 7 Ben Bolker Differences in degrees of freedom between a mixed-effects model and a gls model using nlme Feb 8