Fit logistic regression model — fitLogistic • TrialSimulator

Fit logistic regression model on an binary endpoint.

Refer to this vignette for more information and examples.

Usage

fitLogistic(formula, placebo, data, alternative, scale, ...)

formula: An object of class formula. Must include arm and endpoint in data. Covariates can be adjusted.
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 an odds ratio greater than 1.
scale: character. The type of estimate in the output. Must be one of "coefficient", "log odds ratio", "odds ratio", "risk ratio", or "risk difference". No default value.
...: Subset conditions compatible with dplyr::filter. glm will 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 ~ arm, 'pbo', data, 'greater', 'odds ratio', arm %in% c('pbo', 'low dose'), cfb > 0.5), which is equivalent to: fitLogistic(remission ~ arm, 'pbo', data, 'greater', 'odds ratio', 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.

a data frame with columns: