pairwiseMEP: Wrapper to compute confidence intervals for multiple...

In pairwiseCI: Confidence Intervals for Two Sample Comparisons

Description

This is a test version! Computes confidence intervals for pair wise comparisons of groups (assuming independent observations) for multiple endpoints. The methods available in pairwiseCI for continuous and count data can be called. Methods for binary data are currently not available. NOTE: Although multiple endpoints and multiple group wise comparisons are considered, there is no adjustment for multiplicity implemented in this function!

Usage

pairwiseMEP(x, ...)

## S3 method for class 'data.frame'
pairwiseMEP(x, ep, f,
 control = NULL, conf.level = 0.95, 
 alternative = c("two.sided", "less", "greater"), 
 method = "Param.diff", ...)

Arguments

x	a data.frame
ep	a vector of character strings, naming the variables in x which are the response variables (endpoints) of interest
f	a single character string, naming a factor variable in data which splits the dataset into treatment groups
control	optionally, a single character string, naming a factor level in variable f, which shall be considered as control group; if omitted (default) all pairwise comparisons are computed
conf.level	a single numeric between 0.5 and 1, specifying the local confidence level of the single confidence intervals
alternative	a single character string, one of 'two.sided', 'less', 'greater'
method	a vector of character strings, specifying the method for computation of the confidence intervals, see pairwiseCImethodsCont and pairwiseCImethodsCount for possible options; must have length 1 or the same length as ep!
...	further arguments to be passed to pairwiseCI, options are listed in pairwiseCImethodsCont and pairwiseCImethodsCount

Details

Calls pairwiseCI.

Value

conf.int	a list with one element for each element in ep, containing the estimates, lower and upper limits and the comparison names and by levels in the format of a data.frame
data	as input x
ep	as input
f	as input
control	as input
conf.level	as input
alternative	as input
method	as input

See Also

The result can be plotted: plotCI.pairwiseMEP, and coerced to a data.frame: as.data.frame.pairwiseMEP

Examples

x1<-rnorm(80,100,8)
x2<-rnbinom(80,mu=10, size=10)
A<-rep(c("a1","a2"), c(40,40))
B<-rep(rep(c("b1","b2"), c(20,20)), times=2)
dat<-data.frame(x1=x1,x2=x2,A=A, B=B)

test<-pairwiseMEP(x=dat, ep=c("x1","x2"), control="a1",
 f="A", by="B", method=c("Param.ratio","Negbin.ratio"))
test


plotCI(test, whichep=c("x1","x2"))

as.data.frame(test, whichep=c(1,2))

as.data.frame(test, whichep=c("x1","x2"))

pairwiseCI documentation built on May 1, 2019, 6:51 p.m.