tidysummary (version 0.1.0)

small_test: Check Sample Size Adequacy for Chi-Squared Test

Description

This function determines if a contingency table meets the expected frequency assumptions for a valid chi-squared test. It categorizes the data into "not_small", "small", or "very_small" based on sample size and expected frequencies.

Usage

small_test(data, var, group)

Value

A character string with one of three values:

• "not_small": Sample size more than or euqal to 40 and all expected frequencies more than or euqal to 5

• "small": Sample size more than or euqal to 40, all expected frequencies more than or euqal to 1 and at least one <5, only for 2*2 contingency tables

• "very_small": Other conditions, including sample size <40 or any expected frequency <1

Arguments

data

A data frame containing the variables to be tested.

var

A character string specifying the factor variable in data to test.

group

A character string specifying the grouping variable in data.

Examples

df <- data.frame(
  category = factor(c("A", "B", "A", "B")),
  group    = factor(c("X", "X", "Y", "Y"))
)
small_test(data = df, var = "category", group = "group")