My experience has been that different texts will give slightly different
formulas for calculating d.f. at levels 1 and 2, but since all formulas only
give approximations getting the "exact right" number of d.f. really
shouldn't be the goal.   In terms of references, some places to look are:


West, Brady T., Kathleen B. Welch, and Andrzej T. Galecki. 2007. *Linear
Mixed Models: A Practical Guide Using Statistical Software*. Boca Raton,
F.L. Chapman and Hall/CRC.

Bickel, Robert. 2007. *Multilevel Analysis for Applied Research: Itʼs Just
Regression!* Guilford Press.


A briefer but less social science oriented approach can be found in:


Crawley, Michael J. 2007. *The R Book*. Chichester, England: John Wiley &
Sons Ltd. [chapter 19]


These texts provide accessible treatments of linear mixed models, with some
attention to the issue of d.f.  A more advanced treatment can be found in:


Raudenbush, Stephen W., and Anthony S. Bryk. 2002. *Hierarchical Linear
Models: Applications and Data Analysis Methods*. 2nd ed. Thousand Oaks, C.A.
Sage Publications.

On Tue, May 10, 2011 at 8:14 AM, Zofia Prokop <zofia.prokop@uj.edu.pl>wrote:

> Hello,
>
> I'm wondering how to obtain df-s associated with t values for fixed factors
> in lmer. I need them in order to calculate the effect sizes (Pearson's r)
> for those fixed factors.
>
> One method of calculating df number I came across is to take the total
> number of observation minus the number(s) of levels of random factor(s).
> But
> I have my doubts, such as
>
> (1) what about the number of fixed factors in the model - shouldn't it be
> subtracted as well?
>
> (2) I can see how this method can be applied to models where random factors
> are crossed with fixed factors but what about when they are nested? Or in
> case of more comlex designs? The model I'm struggling with at the moment is
> such:
> I have 10 females and 10 males crossed in a full factorial design,
> resulting
> in 100 offspring trait means (one per each pairing). Fixed factors are:
> female category and male category (2 levels each). I'm fitting a model:
>
> siz <- lmer(sz~femcat+malecat+(1|femid)+(1|maleid))
>
> What about those df-s for femcat and malecat?
>
> I'd be very grateful for advice as well as literature suggestions (I'm very
> new to mixed modelling and trying to get my head around it).
>
> -Zofia
>
> --
> --
> Zofia Maria Prokop
> PhD student
> Molecular and Behavioral Ecology Group
> Jagiellonian University
> Gronostajowa 7
> 30-387 Krakow, Poland
> zofia.prokop@uj.edu.pl
>
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>
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