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
.
1 2 3 4 5  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, ...)

formula 
A formula of the structure response ~ treatment for numerical variables, and of structure cbind(success, failure) ~ treatment for binomial variables 
data 
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. 
alternative 
Character string, either "two.sided", "less" or "greater" 
conf.level 
The comparisonwise confidence level of the intervals, where 0.95 is default 
method 
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 t.test.ratio(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 HodgesLehmann estimator,
"HL.ratio": Exact nonparametric CI for ratio of locations, based on the HodgesLehmann 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 
control 
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 
These functions are for internal use in pairwiseCI.
a list containing:
estimate 
numeric vector: the point estimates 
lower 
numeric vector: lower confidence bounds 
upper 
numeric vector: upper confidence bounds 
compnames 
character vector with the names of comparisons 
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 manytoone comparisons
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
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