split_pilot_set: Split data into pilot and analysis sets

In raikens1/stratamatch: Stratification and Matching for Large Observational Data Sets

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
)

raikens1/stratamatch documentation built on April 1, 2022, 9:48 p.m.