confint.clusbootglm: Confidence intervals for cluster bootstrap model parameters

In ClusterBootstrap: Analyze Clustered Data with Generalized Linear Models using the Cluster Bootstrap

Description

Computes confidence intervals for one or more parameters in a fitted GLM with the cluster bootstrap.

Usage

## S3 method for class 'clusbootglm'
confint(object, parm = "all", level = 0.95, interval.type = "BCa", ...)

Arguments

object	object of class clusbootglm.
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. Defaults to all parameters.
level	the required confidence level
interval.type	type of confidence level. Options are BCa, percentile, and parametric.
...	other arguments.

Author(s)

Mathijs Deen

Examples

## Not run: 
data(opposites)
cbglm.1 <- clusbootglm(SCORE~Time*COG,data=opposites,clusterid=Subject)
confint(cbglm.1,parm=c("Time","COG"), level=.90, interval.type="percentile")
## End(Not run)

Example output

Loading required package: parallel
Loading required package: magrittr
Loading required package: dplyr

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

            5%        95%
Time 28.864687 35.7684966
COG  -0.872827  0.9400413

ClusterBootstrap documentation built on Feb. 16, 2021, 5:06 p.m.