cg (version 0.9.0)

grpSummaryTable.cgOneFactorFit: Create a table of estimated group means and variability with a cgOneFactorFit object.

Description

Create a table of estimated group means based on the cgOneFactorFit object. Standard errors and confidence intervals are added. A cgOneFactorGrpSummaryTable class object is created.

Usage

## S3 method for class 'cgOneFactorFit':
grpSummaryTable(fit, mcadjust=FALSE, alpha=0.05, display="print",  ...)

Arguments

fit

A fit 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

alpha

Significance level, by default set to 0.05.

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 relevant

Value

• Creates an object of class cgOneFactorGrpSummaryTable, 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 group name (factor level), and these columns: [object Object],[object Object],[object Object],[object Object]

concept

• group summary
• 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 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)

grpSummaryTable(canine.fit)

grpSummaryTable(canine.fit, mcadjust=TRUE, model="olsonly")


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

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

grpSummaryTable(gmcsfcens.fit)