[R-sig-ME] lmer versus glm results

[Yuqing Ren]

Dear All,

I have a quick questions about comparing results from lmer and from
glm. We are running analysis to predict a person's likelihood of
leaving a project with some people affiliated with multiple projects
(binary outcome and crossed random effects).

The data consist of three levels: projects, members (crossed with
projects with 70% members with one project and 30% with multiple
projects), and time series nested within individuals. I ran the
analysis with first glm (family=binomial) and then lmer
(family-binomial and + (1 | projectid) + (1 | memberid) to account for
the random effects). The two analyses have the same covariates:
project size and scope and some individual member attributes such as
tenure and past performance.

Theoretically, I expect the coefficients to be similar between the two
results with some differences in the significance test or confidence
intervals. However, I found three coefficients flipped signs between
the two, which is very puzzling. I ran another set of analysis with a
continuous dependent variable (quantity of work completed) and found
similar coefficients between the two (results from lm and lmer).

So my question is: should we expect the results from glm and lmer to
be similar? If we should see different results, is it because of the
distribution being binomial rather than normal or other reasons? Which
set of results is more reliable and should be included in our paper?

Thanks very much.

Ching Ren