Paired Samples Contingency Tables — contTablesPaired • ClinicoPath

McNemar test

Usage

contTablesPaired(
  data,
  rows,
  cols,
  counts = NULL,
  chiSq = TRUE,
  chiSqCorr = FALSE,
  exact = FALSE,
  pcRow = FALSE,
  pcCol = FALSE,
  formula
)

Arguments

data: the data as a data frame
rows: the variable to use as the rows in the contingency table (not necessary when providing a formula, see the examples)
cols: the variable to use as the columns in the contingency table (not necessary when providing a formula, see the examples)
counts: the variable to use as the counts in the contingency table (not necessary when providing a formula, see the examples)
chiSq: TRUE (default) or FALSE, provide X²
chiSqCorr: TRUE or FALSE (default), provide X² with continuity correction
exact: TRUE or FALSE (default), provide an exact log odds ratio (requires exact2x2 to be installed)
pcRow: TRUE or FALSE (default), provide row percentages
pcCol: TRUE or FALSE (default), provide column percentages
formula: (optional) the formula to use, see the examples

Value

A results object containing:

`results$freqs`					a proportions table
`results$test`					a table of test results

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$freqs$asDF

as.data.frame(results$freqs)

Examples

dat <- data.frame(
    `1st survey` = c('Approve', 'Approve', 'Disapprove', 'Disapprove'),
    `2nd survey` = c('Approve', 'Disapprove', 'Approve', 'Disapprove'),
    `Counts` = c(794, 150, 86, 570),
    check.names=FALSE)

contTablesPaired(formula = Counts ~ `1st survey`:`2nd survey`, data = dat)

#
#  PAIRED SAMPLES CONTINGENCY TABLES
#
#  Contingency Tables
#  ------------------------------------------------
#    1st survey    Approve    Disapprove    Total
#  ------------------------------------------------
#    Approve           794           150      944
#    Disapprove         86           570      656
#    Total             880           720     1600
#  ------------------------------------------------
#
#
#  McNemar Test
#  -----------------------------------------------------
#                                Value    df    p
#  -----------------------------------------------------
#    X²                           17.4     1    < .001
#    X² continuity correction     16.8     1    < .001
#  -----------------------------------------------------
#


# Alternatively, omit the left of the formula (`Counts`) from the
# formula if each row represents a single observation:

contTablesPaired(formula = ~ `1st survey`:`2nd survey`, data = dat)