stratify: Stratify a Population Data Frame

In katiecoburn/generalizeR: What the Package Does (One Line, Title Case)

Description

This function takes as input any data frame that you want to stratify into clusters. Typically, the goal of such stratification is sampling for generalizability. This function, and the others in this package, are designed to mimic the website https://www.thegeneralizer.org/.

Usage

stratify(data, guided = TRUE, n_strata = NULL, variables = NULL, idnum = NULL)

Arguments

data	The R object containing your population data frame
guided	logical; defaults to TRUE. Whether the function should be guided (ask questions and behave interactively throughout) or not. If set to FALSE, must provide values for other arguments below
n_strata	defaults to NULL. If guided is set to FALSE, must provide a number of strata to cluster population into
variables	defaults to NULL. If guided is set to FALSE, must provide a character vector of the names of stratifying variables (from population data frame)
idnum	defaults to NULL. If guided is set to FALSE, must provide a character vector of the name of the ID variable (from population data frame)

Details

The list contains 11 components: x2, solution, n_strata, recruitment_lists, population_summary_stats2, summary_stats, summary_stats2, heat_data, heat_plot_final, idnum, and variables.

• x2: a tibble with number of rows equal to the number of rows in the inference population (data) and number of columns equal to the number of stratifying variables (dummy-coded if applicable) plus the ID column (idnum) and a column representing stratum membership, clusterID

Value

The function returns a list of class "generalizer_output" that can be provided as input to recruit(). More information on the components of this list can be found above under "Details."

References

Tipton, E. (2014). Stratified sampling using cluster analysis: A sample selection strategy for improved generalizations from experiments. Evaluation Review, 37(2), 109-139.

Tipton, E. (2014). How generalizable is your experiment? An index for comparing experimental samples and populations. Journal of Educational and Behavioral Statistics, 39(6), 478-501.

Examples

## Not run: 
# To get sample data; must first be installed using install_github("katiecoburn/generalizeRdata")
library(generalizeRdata)

# Guided:
stratify(ipeds)

# Not guided:
stratify(ipeds, guided = FALSE, n_strata = 4,
   variables = c("pct_female", "pct_white"), idnum = "unitid")

## End(Not run)

katiecoburn/generalizeR documentation built on Oct. 28, 2020, 4:43 a.m.