cg (version 1.0-0)

comparisonsTable: Create a Table of Comparisons amongst Groups

Description

Create a table of comparisons based on a fit by the cg package.

Usage

comparisonsTable(fit, type = "pairwisereflect", alpha = 0.05, addpct = FALSE,
 display = "print", ...)

Arguments

fit

A fit object created with a fit method from the cg package. See specific methods.

type

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

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, depending on the specific method written for the object. See the method-specific documentation for additional details.

Value

• A method-specific comparisonsTable object is returned. See the specific methods for discussion of return values.

concept

• comparisons
• multiplicity

See Also

comparisonsTable.cgOneFactorFit, comparisonsTable.cgPairedDifferenceFit.

Examples

#### One Factor data

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)

## Paired Difference data

data(anorexiaFT)
anorexiaFT.data <- prepareCGPairedDifferenceData(anorexiaFT, format="groupcolumns",
                                                 analysisname="Anorexia FT",
                                                 endptname="Weight",
                                                 endptunits="lbs",
                                                 expunitname="Patient",
                                                 digits=1,
                                                 logscale=TRUE)
anorexiaFT.fit <- fit(anorexiaFT.data)

comparisonsTable(anorexiaFT.fit)