Farrington-Manning test for rate difference
Source:R/fitFarringtonManning.R
fitFarringtonManning.RdTest rate difference by comparing it to a pre-specified value using the Farrington-Manning test.
Refer to this vignette for more information and examples.
Arguments
- endpoint
Character. Name of the endpoint in
data.- placebo
Character. String indicating the placebo in
data$arm.- data
Data frame. Usually it is a locked data set.
- alternative
a character string specifying the alternative hypothesis, must be one of
"greater"or"less", i.e., one-sided test is enforced. No default value."greater"means superiority of treatment over placebo is established by rate difference greater than `delta`.- ...
Subset conditions compatible with
dplyr::filter.glmwill be fitted on this subset only. This argument can be useful to create a subset of data for analysis when a trial consists of more than two arms. By default, it is not specified, all data will be used to fit the model. More than one condition can be specified in..., e.g.,fitFarringtonManning('remission', 'pbo', data, delta, arm %in% c('pbo', 'low dose'), cfb > 0.5), which is equivalent to:fitFarringtonManning('remission', 'pbo', data, delta, arm %in% c('pbo', 'low dose') & cfb > 0.5). Note that if more than one treatment arm are present in the data after applying filter in..., models are fitted for placebo verse each of the treatment arms.- delta
the rate difference between a treatment arm and placebo under the null. 0 by default.
Value
a data frame with three columns:
armname of the treatment arm.
placeboname of the placebo arm.
estimateestimate of rate difference.
pone-sided p-value for log odds ratio (treated vs placebo).
infosample size in the subset with
NAbeing removed.zthe z statistics of log odds ratio (treated vs placebo).