specifying crossed random effects for glmmPQL / lme

Thanks for your response, Ben! The paper that argued the use of the
identity link with Gamma for response time data is Lo & Andrews (2015) (doi:
10.3389/fpsyg.2015.01171 <https://dx.doi.org/10.3389%2Ffpsyg.2015.01171>).
Would such a model still be computationally problematic if the observed
values fall very much within the domain of the specified probability
distribution (i.e., valid response times are always above 200 ms)?

Re: "allow for correlations of random effects to be estimated", I've been
told that it's more tractable to estimate covariances between the random
slopes and intercepts (as I want with my model) using PQL than
Laplace/AGHQ. In fact, Lo & Andrews' demonstration using glmer explicitly
specified the covariances between the slopes and the intercepts to be 0 due
to the computational rigor of specifying a model with random
intercept-slope covariances in glmer and due to theoretical reasons.

And thanks for pointing out the Pinheiro & Bates (2000) reference to
specifying crossed effects!

Sincerely,
Van Liceralde

Van Rynald T. Liceralde, BS, BA
Graduate Student, Cognitive Psychology
University of North Carolina at Chapel Hill

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