Learn R Programming

pairwiseCI (version 0.1-27)

QBmover: Confidence intervals for ratios of proportions based on the quasibinomial assumption

Description

Confidence intervals for ratios of proportions with overdispersed binomial data in a one-factor quasibinomial generalized linear model. Intervals are computed using the MOVER-R method on profile deviance intervals (as implemented in mcprofile) for the single proportions.

Usage

QBmover(succ, fail, trt, conf.level = 0.95,
 alternative = "two.sided", grid = NULL)

Arguments

succ

vector of counts of successes

fail

vector of counts of failures

trt

factor variable distinguishing the treatment groups

conf.level

a single numeric value, the confidence level

alternative

a character string, "two.sided" for two-sided intervals, "less" for upper limits, "greater" for lower limits only

grid

optional, a numeric vector to be supplied to the profiling used internally in quasibin.ratio to obtain profile deviance intervals for each samples proportion on the logit-scale.

Value

A data.frame with three columns

est

estimated ratios

lower

lower confidence limits

upper

upper confidence limits

References

Donner and Zou (2012): Closed-form confidence intervals for functions of the normal mean and standard deviation. Statistical Methods in Medical Research 21(4):347-359. Gerhard (2014): Simultaneous Small Sample Inference For Linear Combinations Of Generalized Linear Model Parameters. Communications in Statistics - Simulation and Computation. DOI:10.1080/03610918.2014.895836

Examples

Run this code
# NOT RUN {
QBmover(succ=c(0,0,1,  0,6,8), fail=c(20,20,18, 20,14,12), 
 trt=factor(rep(c("A", "B"), c(3,3))), conf.level = 0.95,
 alternative = "two.sided", grid = NULL)

# }

Run the code above in your browser using DataLab