Re: [R] compare results of glms

From: Joris Meys <>
Date: Thu, 03 Jun 2010 15:05:23 +0200

Mailing this twice ain't going to help you. Reading a course on statistics might.

The test you want to do is answering following hypothesis : The mean predicted value of a specific model differs when different datasets are used to fit it. Seems likely to me if the datasets are not almost identical. Why testing?

About that Z-test : that should be used in your field of research to test 2 proportions that are not too close to 0 or 1 and that originate from a binomial distribution with large enough n. Suggesting to use it for comparing a number of series of around 20 logit-transformed predicted probabilities is plain shocking.

In case you are interested in the difference of the intercept for these specific trials, add trial as a fixed effect to your model and do the appropriate testing. You want to know whether the relation between state and days differs in slope, you add an interaction term and again use the appropriate testing. To know what is the appropriate testing, see line 1.


On Thu, Jun 3, 2010 at 10:31 AM, Sacha Viquerat <>wrote:

> dear list!
> i have run several glm analysises to estimate a mean rate of dung decay for
> independent trials. i would like to compare these results statistically but
> can't find any solution. the glm calls are:
> dung.glm1<-glm(STATE~DAYS, data=o_cov, family="binomial(link="logit"))
> dung.glm2<-glm(STATE~DAYS, data=o_cov_T12, family="binomial(link="logit"))
> as all the trials have different sample sizes (around 20 each),
> anova(dung.glm1, dung.glm2)
> is not applicable. has anyone an idea?
> thanks in advance!
> ps: my advisor urges me to use the z-test (the common test statistic in my
> field of research), but i reject that due to the small sample size.
> ______________________________________________
> mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.

Joris Meys
Statistical Consultant

Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control

Coupure Links 653
B-9000 Gent

tel : +32 9 264 59 87
Disclaimer :

	[[alternative HTML version deleted]]

______________________________________________ mailing list
PLEASE do read the posting guide
and provide commented, minimal, self-contained, reproducible code.
Received on Thu 03 Jun 2010 - 13:07:36 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Thu 03 Jun 2010 - 13:20:27 GMT.

Mailing list information is available at Please read the posting guide before posting to the list.

list of date sections of archive