RE: [R] ANOVA procedure on the sufficient statistics
You can apply the trick that Prof. Dalgaard recently posted in response to a similar question (for one-way ANOVA). For each cell, generate data as: y - cell.mean + cell.sd * scale(rnorm(cell.count)) Then generate the data frame to feed to aov. That will generate only approximately the same means and MSE, however. Larsen's procedure generates a weighted data set that gives the same ANOVA table as the raw data, but requires that the weight= argument be used in aov(). (weights are not supported in all related functions) -Michael -- Michael Friendly Email: [EMAIL PROTECTED] Professor, Psychology Dept. York University Voice: 416 736-5115 x66249 Fax: 416 736-5814 4700 Keele Streethttp://www.math.yorku.ca/SCS/friendly.html Toronto, ONT M3J 1P3 CANADA __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] ANOVA procedure on the sufficient statistics
On Thu, 19 Feb 2004 08:45:01 -0500, Michael Friendly [EMAIL PROTECTED] wrote : You can apply the trick that Prof. Dalgaard recently posted in response to a similar question (for one-way ANOVA). For each cell, generate data as: y - cell.mean + cell.sd * scale(rnorm(cell.count)) Then generate the data frame to feed to aov. That will generate only approximately the same means and MSE, however. Larsen's procedure generates a weighted data set that gives the same ANOVA table as the raw data, but requires that the weight= argument be used in aov(). (weights are not supported in all related functions) Are you sure about that? I think the call to scale() makes them come out identical. In fact, the call to rnorm() is unnecessary; it would work just as well with y - cell.mean + cell.sd * scale(1:cell.count) (unless I'm missing something...) Duncan __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] ANOVA procedure on the sufficient statistics
You can apply the trick that Prof. Dalgaard recently posted in response to a
similar question (for one-way ANOVA). For each cell, generate data as:
y - cell.mean + cell.sd * scale(rnorm(cell.count))
Then generate the data frame to feed to aov.
HTH,
Andy
From: Yun-Fang Juan
Hi,
I have a two-way anova with unequal cell numbers that I want
to analyze.
The problem is I don't have individual observations of the data.
I only have the sufficient statistics (mean, variance, # of
observations) for each cell.
Is there any existing function in S-plus that would allow me
to do aov() with the sufficient statistics?
The table is like
G1 G2 G3 G5 G6
T1
T2
T3
For cell (Ti, Gj) i have mean, variance and # observations
and the factors are unordered.
Thanks a lot for helping me on this in advance.
Yun-Fang
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re: [R] ANOVA procedure on the sufficient statistics
Hi, I have a two-way anova with unequal cell numbers that I want to analyze. The problem is I don't have individual observations of the data. I only have the sufficient statistics (mean, variance, # of observations) for each cell. Is there any existing function in S-plus that would allow me to do aov() with the sufficient statistics? See: David Larsen, Analysis of Variance With Just Summary Statistics as Input, The American Statistician, May 1992, Vol. 46(2), 151-152. This is implemented in SAS, Doc: http://www.math.yorku.ca/SCS/sasmac/stat2dat.html Shouldn't be hard to do in R. -- Michael Friendly Email: [EMAIL PROTECTED] Professor, Psychology Dept. York University Voice: 416 736-5115 x66249 Fax: 416 736-5814 4700 Keele Streethttp://www.math.yorku.ca/SCS/friendly.html Toronto, ONT M3J 1P3 CANADA __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
