On Tue, Feb 1, 2011 at 10:51 AM, Luana Marotta <lucsmaro...@gmail.com> wrote: > Dear R-users,
> I'm running a lmer model using the lme4 package. My dependent variable is > dichotomous and I'm using the "binomial" family. The results > are slightly different from the HLM results based on a Bernoulli > distribution. I read that a Bernoulli distribution is an extension of a > binomial distribution. Is that right? If so, how can I adapt my R model to a > Bernoulli distribution so that my R results are the same as my HLM results? Actually it's the other way around. A binomial(n, p) random variable is the sum of n independent Bernoulli(p) random variables. Alternatively, you could describe the Bernoulli(p) distribution as a special case of the binomial, the binomial(1, p) distribution. It is generally more productive to ask questions regarding lme4 and lmer on the r-sig-mixed-mod...@r-project.org mailing list. It would help if you could make the data and the output of your model fits available so we can check on different systems. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
