Confidence Intervals for Two Sample Comparisons
Coercing pairwiseCI objects to data.frames
Coerce pairwiseMEP objects to data.frames
MOVER-R method by Donner and Zhou (2012)
Nonparametric test and confidence interval based on relative effects
Confidence intervals for risk ratios of overdispersed binomial data
Wrapper functions for two-sample confidence intervals and tests.
Wrapper function for two-sample confidence intervals
Internal functions for pairwiseCI
Confidence intervals for two sample comparisons of continuous data
Confidence intervals for two sample comparisons of count data
Confidence intervals for two sample comparisons of binomial proportion...
Wrapper to compute confidence intervals for multiple endpoints
Wrapper to calculate unadjusted p-values for pairwise comparisons
Internal functions for pairwiseTest
Plotting the output of pairwiseCI
Plot confidence intervals
Print function for "pairwiseCI"
Print function for "pairwiseTest"
Print function for "summary.pairwiseCI"
Print function for "summary.pairwiseTest"
Construct a (quasi-) likelihood-profile
Wrapper to prop.test(stats)
Confidence intervals for ratios of proportions based on the quasibinom...
Summary function for pairwiseCI
Summary function for "pairwiseTest"
Calculation of the parametric, nonparametric confidence intervals for the difference or ratio of location parameters, nonparametric confidence interval for the Behrens-Fisher problem and for the difference, ratio and odds-ratio of binomial proportions for comparison of independent samples. Common wrapper functions to split data sets and apply confidence intervals or tests to these subsets. A by-statement allows calculation of CI separately for the levels of further factors. CI are not adjusted for multiplicity.