ExtractCI {postHoc}

Calculates the Wald or a parametric bootstrap confidence intervals for GLMs and GLMMs

Description

posthoc is used to group or cluster the effects of liner, generalised linear and generalised linear mixed models according to significance of pairwise tests comparing the levels of the effects.

Usage

ExtractCI (Model, EffectIndices = NULL, EffectLabels = NULL,
         ParBootstrap = FALSE, Nboots = 999, digits = 4, coverage = 0.95,
         UpperBound = Inf, SignificanceLevel =  1-coverage,
         EffectsMatrix = NULL, Scale = 1.0, Location = 0.0,
         isBinomialModel = FALSE, BackTransform = TRUE)

Arguments

Model

a model of class lm, glm, glmerMod, lme or gls.

EffectIndices

a vector containing the indices of the effects to be analysed (default = NULL, indicating that all the levels are used).

EffectLabels

a character vector with the labels of the effects (default = NULL, which implies that the corresponding labels of the model coefficient are used).

ParBootstrap

logic flag indicating whether the confidence intervals should be calculated with parametric bootstrap (default is false, i.e. the Wald confidence interval is used).

Nboots

number of bootstrap samples used for the confidence interval. (default = 999).

digits

number of digits used when reporting the results

coverage

the coverage of the confidence intervals (default = 0.95)

UpperBound

an upper bound to the confidence intervals (default = Inf)

SignificanceLevel

the significance level of the pairwise comparisons (default = 0.05).

EffectsMatrix

matrix defining contrasts to be compared (bypasses the EffectIndices, default is NULL, meaning that standard inference is performed).

Scale

a scaling factor multiplying the output table (default = 1, i.e., no scaling is used).

Location

a location term added to the output table (default = 0, i.e., no location shift is performed).

isBinomialModel

a logical flag indicating whther the model is a binomial model different than the Bernoulli (default = FALSE, i.e. not a binomial model).

BackTransform

should the parameters and CIs be back transformed by applying the inverse link function (default = TRUE)

Details

Two possible methos for obtaining confidence intervals are available: Wald confidence intervals and parametric bootstrap confidence intervals.

Value

an object of (S3) class "PostHoc".

a matrix with three columns containing the effects, the lower bound and the upper bound of the confidence intervals for the effects.

Author(s)

Rodrigo Labouriau

Examples

MM <- glm(Y ~ Treatment+0,  data=DeIdentifiedExample)
ExtractCI (MM)