Fit logistic regression model on an binary endpoint.
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". No default value."greater"means superiority of treatment over placebo is established by an odds ratio greater than 1 because a logistic regression model is fitted withendpoint ~ I(arm != placebo).- ...
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.,fitLogistic('remission', 'pbo', data, arm %in% c('pbo', 'low dose'), cfb > 0.5), which is equivalent to:fitLogistic('remission', 'pbo', data, 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.