Helper functions to test proportion differences

Helper functions to implement various tests on the difference between two proportions.

Usage

prop_chisq(tbl, alternative = c("two.sided", "less", "greater"))

prop_cmh(
  ary,
  alternative = c("two.sided", "less", "greater"),
  diff_se = c("standard", "sato"),
  transform = c("none", "wilson_hilferty")
)

prop_schouten(tbl, alternative = c("two.sided", "less", "greater"))

prop_fisher(tbl, alternative = c("two.sided", "less", "greater"))

Arguments

tbl

(matrix)
matrix with two groups in rows and the binary response (TRUE/FALSE) in columns.

alternative

(string)
whether two.sided, or one-sided less or greater p-value should be displayed.

ary

(array, 3 dimensions)
array with two groups in rows, the binary response (TRUE/FALSE) in columns, and the strata in the third dimension.

diff_se

(string)
either standard or sato; specifies whether to use the Sato variance estimator to calculate the chi-squared statistic.

transform

(string)
either none or wilson_hilferty; specifies whether to apply the Wilson-Hilferty transformation of the chi-squared statistic.

Value

A p-value.

Functions

• prop_chisq(): Performs Chi-Squared test. Internally calls stats::prop.test().

• prop_cmh(): Performs stratified Cochran-Mantel-Haenszel test, using stats::mantelhaen.test() internally. Note that strata with less than two observations are automatically discarded.

• prop_schouten(): Performs the Chi-Squared test with Schouten correction.

• prop_fisher(): Performs the Fisher's exact test. Internally calls stats::fisher.test().

See also

prop_diff_test() for implementation of these helper functions.

Schouten correction is based upon Schouten et al. (1980) .

Examples

# Chi-Squared test
tbl <- matrix(
  c(13, 7, 8, 12),
  nrow = 2,
  byrow = TRUE,
  dimnames = list(group = c("A", "B"), response = c("TRUE", "FALSE"))
)

prop_chisq(tbl)
#> [1] 0.1133944

# Cochran-Mantel-Haenszel test with two strata
ary <- array(
  c(12, 8, 8, 12, 10, 10, 6, 14),
  dim = c(2, 2, 2),
  dimnames = list(
    group = c("A", "B"),
    response = c("TRUE", "FALSE"),
    strata = c("Low", "High")
  )
)

prop_cmh(ary)
#> [1] 0.07437734
#> attr(,"z_stat")
#> [1] -1.784285

# Chi-Squared test with Schouten correction
tbl <- matrix(
  c(13, 7, 8, 12),
  nrow = 2,
  byrow = TRUE,
  dimnames = list(group = c("A", "B"), response = c("TRUE", "FALSE"))
)

prop_schouten(tbl)
#> [1] 0.1594617

# Fisher's exact test
tbl <- matrix(
  c(13, 7, 8, 12),
  nrow = 2,
  byrow = TRUE,
  dimnames = list(group = c("A", "B"), response = c("TRUE", "FALSE"))
)

prop_fisher(tbl)
#> [1] 0.2049272