stratifyByPs uses the provided propensity scores to stratify persons. Additional stratification variables for stratifications can also be used.

stratifyByPs(
population,
numberOfStrata = 5,
stratificationColumns = c(),
baseSelection = "all"
)

## Arguments

population A data frame with the three columns described below How many strata? The boundaries of the strata are automatically defined to contain equal numbers of target persons. Names of one or more columns in the data data.frame on which subjects should also be stratified in addition to stratification on propensity score. What is the base selection of subjects where the strata bounds are to be determined? Strata are defined as equally-sized strata inside this selection. Possible values are "all", "target", and "comparator".

## Value

Returns a date frame with the same columns as the input data plus one extra column: stratumId.

## Details

The data frame should have the following three columns:

 rowId (numeric) A unique identifier for each row (e.g. the person ID) treatment (integer) Column indicating whether the person is in the target (1) or comparator (0) group propensityScore (numeric) Propensity score

## Examples

rowId <- 1:200
treatment <- rep(0:1, each = 100)
propensityScore <- c(runif(100, min = 0, max = 1), runif(100, min = 0, max = 1))
data <- data.frame(rowId = rowId, treatment = treatment, propensityScore = propensityScore)
result <- stratifyByPs(data, 5)