From: Chuck Cleland <ccleland_at_optonline.net>

Date: Tue 16 Jan 2007 - 11:51:25 GMT

Date: Tue 16 Jan 2007 - 11:51:25 GMT

Dawn Ashcourt wrote:

> Hello - I am fairly new to R, (i.e., ability to create functions/write

*> programs insignificant) and was wondering if there might be a convenient way
**> to model the following: I want to fit a gaussian glm to grouped data, while
**> allowing for unequal variances in each of the groups.
**> More specifically, my data set looks something like this:
**> ----------------
**> data group
**> 1 76 1
**> 2 82 1
**> 3 83 1
**> 4 54 1
**> 5 35 1
**> 6 46 1
**> 7 87 1
**> 8 68 1
**> 9 87 2
**> 10 95 2
**> 11 98 2
**> 12 100 2
**> 13 109 2
**> 14 109 2
**> 15 100 2
**> 16 81 2
**> 17 75 2
**> 18 68 2
**> 19 67 2
**> 20 105 3
**> .... et cetera.
**> ---------------
**> There are seven groups in all, each with a different number of observations.
**> The idea is to compare a model in which all the data points can be modeled
**> with a single mean (i.e., if all the group means are equal), or if the data
**> suggests that each of the groups has a different mean. In other words, I
**> want to do a Likelihood ratio test on whether or not the group means are
**> significantly different from each other: the full model would be glm(data ~
**> as.factor(group)-1, family = gaussian), to be compared against a restricted
**> model that only includes an intercept. However, I also need to allow for the
**> fact that each group has a different variance. And this I have no idea how
**> to do. I would really appreciate some help in this matter.
*

Have you considered oneway.test()? For example:

## Not assuming equal variances

oneway.test(breaks ~ tension, data = warpbreaks)

One-way analysis of means (not assuming equal variances)

data: breaks and tension

F = 5.8018, num df = 2.00, denom df = 32.32, p-value = 0.007032

> Thank you in advance,

*> Dawn.
**>
**> [[alternative HTML version deleted]]
**>
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**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
*

-- Chuck Cleland, Ph.D. NDRI, Inc. 71 West 23rd Street, 8th floor New York, NY 10010 tel: (212) 845-4495 (Tu, Th) tel: (732) 512-0171 (M, W, F) fax: (917) 438-0894 ______________________________________________ R-help@stat.math.ethz.ch 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.Received on Tue Jan 16 22:57:55 2007

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