For internal use. Two different methods for data representable as a two numeric vectors (pairwiseCICont) and
data representable as matrix with two columns like cbind(successes, failures).
Functions that split up a data.frame according to one factor, and perform all pairwise comparisons
and comparisons to control among the levels of the factor by calling methods documented in pairwiseCImethodsCont
and pairwiseCImethodsProp.
pairwiseCICont(formula, data, alternative="two.sided",
conf.level=0.95, method, control=NULL, ...)pairwiseCIProp(formula, data, alternative="two.sided",
conf.level=0.95, control=NULL, method, ...)
A formula of the structure response ~ treatment for numerical variables, and of structure cbind(success, failure) ~ treatment for binomial variables
A data.frame containing the numerical response variable and the treatment and by variable as factors. Note, that for binomial data, two columns containing the number of successes and failures must be present in the data.
Character string, either "two.sided", "less" or "greater"
The comparisonwise confidence level of the intervals, where 0.95 is default
A character string specifying the confidence interval method, one of the following options
"Param.diff": Difference of two means, with additional argument var.equal=FALSE(default) as in t.test(stats)
"Param.ratio": Ratio of two means, with additional argument var.equal=FALSE(default) as in ttestratio(mratios)
"Lognorm.diff": Difference of two means, assuming a lognormal distribution,
"Lognorm.ratio": Ratio of two means, assuming a lognormal distribution,
"HL.diff": Exact nonparametric CI for difference of locations based on the Hodges-Lehmann estimator,
"HL.ratio": Exact nonparametric CI for ratio of locations, based on the Hodges-Lehmann estimator,
"Median.diff": Nonparametric CI for difference of locations, based on the medians (percentile bootstrap CI),
"Median.ratio": Nonparametric CI for ratio of locations, based on the medians (percentile bootstrap CI),
"Prop.diff": Asymptotic CI for difference of proportions prop.test(stats)
"Prop.ratio": Asymptotic CI for ratio of proportions
"Prop.or": Asymptotic CI for the odds ratio
See ?pairwiseCImethods for details.
Character string, specifying one of the levels of the treatment variable as control group in the comparisons; default is NULL, then CI for all pairwise comparisons are calculated.
further arguments to be passed to the functions specified in methods
a list containing:
numeric vector: the point estimates
numeric vector: lower confidence bounds
numeric vector: upper confidence bounds
character vector with the names of comparisons
These functions are for internal use in pairwiseCI.
pairwiseCI for the user level function;
pairwiseCImethodsCont, and pairwiseCImethodsProp for a more detailed documentation of the implemented methods;
summary.pairwiseCI for a summary function.
t.test(stats), wilcox.exact(exactRankTests), prop.test(stats) for the sources of some of the CI methods, multcomp for simultaneous intervals for difference for various contrasts, mratios for simultaneous intervals for the ratio in many-to-one comparisons