split_pilot_set {stratamatch}

Split data into pilot and analysis sets

Description

Given a data set and some parameters about how to split the data, this function partitions the data accordingly and returns the partitioned data as a list containing the analysis_set and pilot_set.

Usage

split_pilot_set(
  data,
  treat,
  pilot_fraction = 0.1,
  pilot_size = NULL,
  group_by_covariates = NULL
)

Arguments

data

data.frame with observations as rows, features as columns

treat

string giving the name of column designating treatment assignment

pilot_fraction

numeric between 0 and 1 giving the proportion of controls to be allotted for building the prognostic score (default = 0.1)

pilot_size

alternative to pilot_fraction. Approximate number of observations to be used in pilot set. Note that the actual pilot set size returned may not be exactly pilot_size if group_by_covariates is specified because balancing by covariates may result in deviations from desired size. If pilot_size is specified, pilot_fraction is ignored.

group_by_covariates

character vector giving the names of covariates to be grouped by (optional). If specified, the pilot set will be sampled in a stratified manner, so that the composition of the pilot set reflects the composition of the whole data set in terms of these covariates. The specified covariates must be categorical.

Value

a list with analaysis_set and pilot_set

Examples

dat <- make_sample_data()
splt <- split_pilot_set(dat, "treat", 0.2)
# can be passed into auto_stratify if desired
a.strat <- auto_stratify(splt$analysis_set, "treat", outcome ~ X1,
  pilot_sample = splt$pilot_set
)