multcomp.wrapper: Simultaneous confidence intervals for arbitrary parametric...

In mutoss: Unified Multiple Testing Procedures

Simultaneous confidence intervals for arbitrary parametric contrasts in unbalanced one-way layouts.

Description

Simultaneous confidence intervals for arbitrary parametric contrasts in unbalanced one-way layouts. The procedure controls the FWER in the strong sense.

Usage

multcomp.wrapper(model, hypotheses, alternative, rhs=0, alpha, factorC)

Arguments

model	a fitted model, for example an object returned by lm, glm, or aov etc. It is assumed that coef and vcov methods are available for model.
hypotheses	a specification of the linear hypotheses to be tested.
alternative	a character string specifying the alternative hypothesis, must be one of 'two.sided' (default), 'greater' or 'less'.
rhs	an optional numeric vector specifying the right hand side of the hypothesis.
alpha	the significance level
factorC	character string, specifing the factor variable of interest

Details

this function, it is possible to compute simultaneous confidence for arbitrary parametric contrasts in the unbalanced one way layout. Moreover, it computes p-values. The simultaneous confidence intervals are computed using multivariate t-distribution.

Value

A list containing:

adjPValues	A numeric vector containing the adjusted pValues
rejected	A logical vector indicating which hypotheses are rejected
confIntervals	A matrix containing the estimates and the lower and upper confidence bound
errorControl	A Mutoss S4 class of type errorControl, containing the type of error controlled by the function.

Author(s)

MuToss-Coding Team

Examples

data(warpbreaks)
# Tukey contrast on the levels of the factor 'Tension'

multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), 
  hypotheses = "Tukey", alternative="two.sided", factorC="tension",alpha=0.05)

# Williams contrast on 'Tension'
multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), 
  hypotheses= "Williams", alternative="two.sided",alpha=0.05,factorC="tension")

# Userdefined contrast matrix
K <-matrix(c(-1,0,1,-1,1,0, -1,0.5,0.5),ncol=3,nrow=3,byrow=TRUE)
multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), 
  hypotheses=K, alternative="two.sided",alpha=0.05,factorC="tension")

# Two-way anova
multcomp.wrapper(aov(breaks ~ tension*wool, data = warpbreaks), 
  hypotheses="Tukey", alternative="two.sided",alpha=0.05,factorC="wool")
multcomp.wrapper(aov(breaks ~ tension*wool, data = warpbreaks), 
  hypotheses="Tukey", alternative="two.sided",alpha=0.05,factorC="tension")
multcomp.wrapper(aov(breaks ~ tension*wool, data = warpbreaks), 
  hypotheses=K, alternative="two.sided",alpha=0.05, factorC="tension")
data(iris)
multcomp.wrapper(model=lm(Sepal.Length ~ Species, data=iris), 
  hypotheses="Tukey","two.sided",alpha=0.05, factorC="Species")
K <-matrix(c(-1,0,1,-1,1,0, -1,0.5,0.5),ncol=3,nrow=3,byrow=TRUE)
multcomp.wrapper(model=lm(Sepal.Length ~ Species, data=iris),
  hypotheses=K,"two.sided",alpha=0.05, factorC="Species")

mutoss documentation built on March 31, 2023, 8:46 p.m.