cg (version 0.9-2)

comparisonsTable.cgOneFactorFit: Create a table of comparisons amongst groups with the cgOneFactorFit object

Description

Create a table of comparisons based on the cgOneFactorFit object. Pairwise or custom specified contrasts are estimated and tested. A cgOneFactorComparisonsTable class object is created.

Usage

## S3 method for class 'cgOneFactorFit':
comparisonsTable(fit, mcadjust=FALSE, type="pairwisereflect",
 contrastmatrix=NULL, refgrp=NULL, alpha=0.05, addpct=FALSE,
 display="print", \dots)

Arguments

fit

An object of class cgOneFactorFit.

mcadjust

Do a multiple comparisons adjustment, based on the simultaneous inference capabilities of the multcomp package. See Details below. The default value is FALSE. If mcadjust=TRUE is specified, there will be

type

Can be one of four values: [object Object],[object Object],[object Object],[object Object]

contrastmatrix

Only relevant if type="custom" is specified. In that case, a numeric matrix with the number of rows equal to the number of comparisons of interest. The number of columns must be equal to the number of group means. Each row in

refgrp

If left at the default value of NULL, it will be set to the settings$refgrp value in the cg fit object. When set, it is deemed the "reference", or "control" group, so that pairwise compariso

alpha

Significance level, by default set to 0.05.

addpct

Only relevant if settings$endptscale=="original" in the fit object. An column of percent differences is added for the comparisons, as a descriptive supplement to the original scale differences that are formally estimated.

display

One of three valid values: [object Object],[object Object],[object Object]

...

Additional arguments. Only one is currently valid: [object Object] For other possible cgOneFactorFit fit components such as accelerated failure time or unequal variance models, the model argument is not relev

Value

• Creates an object of class cgOneFactorComparisonsTable, with the following slots: [object Object],[object Object],[object Object],[object Object],[object Object] The data frame structure of the comparisons table in a *.comprs slot consists of row.names that specify the comparison of the form A vs. B, and these columns: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object] An additional column addpct of percent differences is added if endptscale=="original" and addpct=TRUE, as a descriptive supplement to the original scale differences that are formally estimated.

concept

• comparisons
• multiplicity

Details

When mcadjust=TRUE, a status message of "Some time may be needed as the critical point from the multcomp::summary.glht function call is calculated" is displayed at the console. This computed critical point is used for all subsequent p-value and confidence interval calculations. The multcomp package provides a unified way to calculate critical points based on the comparisons of interest in a "family". Thus a user does not need to worry about choosing amongst the myriad names of multiple comparison procedures.

References

Hothorn, T., Bretz, F., Westfall, P., Heiberger, R.M., and Schuetzenmeister, A. (2010). The multcomp package. Hothorn, T., Bretz, F., and Westfall, P. (2008). "Simultaneous Inference in General Parametric Models", Biometrical Journal, 50, 3, 346-363.

Examples

data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
                                      analysisname="Canine",
                                      endptname="Prostate Volume",
                                      endptunits=expression(plain(cm)^3),
                                      digits=1, logscale=TRUE, refgrp="CC")
canine.fit <- fit(canine.data)

canine.comps0 <- comparisonsTable(canine.fit)

canine.comps1 <- comparisonsTable(canine.fit,  mcadjust=TRUE,
                                   type="allgroupstocontrol", refgrp="CC")


data(gmcsfcens)
gmcsfcens.data <- prepareCGOneFactorData(gmcsfcens, format="groupcolumns",
                                         analysisname="cytokine",
                                         endptname="GM-CSF (pg/ml)",
                                         logscale=TRUE)

gmcsfcens.fit <- fit(gmcsfcens.data, type="aft")

gmcsfcens.comps <- comparisonsTable(gmcsfcens.fit)