Logistics Linear Regression — logistic_regression • mirrorstoolkit

A wrapper creating logistic regression formula and clean the output

Usage

logistic_regression(
  data,
  variable,
  response,
  adjustments,
  mode = "table",
  with_power = FALSE,
  variable_distribution = "normal"
)

data: data.frame the table working on
variable: str, the name of column of interested variable in table data
response: str, the name of column of target variable in table data
adjustments: vector of str, the list of adjustment variables in the table data
mode: str, when "summary", only output the coefficient corresponding to column specified in variable
with_power: boolean, when set to TRUE, will call pwrss.z.logreg function computing the power and sample size at 80 percent power, default FALSE to save computation burden
variable_distribution: str, either "normal" or "binary", the distribution of variable of interest specified, only necessary when with_power = TRUE, default "normal"

data.frame, if mode summary, only the beta and p-value(z-value) for variable specified in "variable", otherwise the general summary()