Re: [R] split-plot multiple comparisons

From: Richard M. Heiberger <>
Date: Fri 05 Jan 2007 - 20:09:08 GMT

Thank you for your example. I am now using it an example in the MMC Mean--mean Multiple Comparisons plot in the HH package on CRAN. The source for HH_1.17 is on CRAN in Austria as of this morning. The Windows and MacOS binaries will be on CRAN in a few days and will then propagate to the mirrors.

Until then, you can get the R Windows binary directly from me at          ## R Windows binary       ## source ## S-Plus 8 Windows binary

The S-Plus 8 package is also available at

After you install and load HH with

?MMC will give the complete example.

Some comments on the example.

The first interaction2wt figure shows parallel traces in the blocks, visually confirming that the blocks appear to be orthogonal to the treatments.

The second interaction2wt figure shows a hint of the hibrido:nitrogeno interaction since the P3732 trace is monotone increasing in nitrogen and the others bend back.

The MMC plot shows very clearly that the hybrids fall into two different groups, with LH74, P3747, and P3732 in one group and with Mol17 and A632 in the other group. There is a non-significant distinction between LH74 and the two P37** varieties.

The MMC plot needs the tiebreaker in this example because observed means for several of the groups are almost identical.

The MMC plot is described in

Journal of Computational & Graphical Statistics 2006, vol. 15, no. 4, pp. 937 - 955
Mean-Mean Multiple Comparison Displays for Families of Linear Contrasts Richard M. Heiberger; Burt Holland

Traditional tabular and graphical displays of results of simultaneous confidence intervals or hypothesis tests are deficient in several respects. Expanding on earlier work, we present new mean-mean multiple comparison graphs that succinctly and compactly display the results of traditional procedures for multiple comparisons of population means or linear contrasts involving means. The MMC plot can be used with unbalanced, multifactor designs with covariates. After reviewing the construction of these displays in the S language (S-Plus and R), we demonstrate their application to four multiple comparison scenarios. mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Sat Jan 06 12:10:27 2007

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