contTables: Contingency Tables
In jmv: The 'jamovi' Analyses

contTables

R Documentation

Contingency Tables

Description

The X² test of association (not to be confused with the X² goodness of fit) is used to test whether two categorical variables are independent or associated. If the p-value is low, it suggests the variables are not independent, and that there is a relationship between the two variables.

Usage

contTables(data, rows, cols, counts = NULL, layers = NULL,
  chiSq = TRUE, chiSqCorr = FALSE, zProp = FALSE, likeRat = FALSE,
  fisher = FALSE, contCoef = FALSE, phiCra = FALSE,
  diffProp = FALSE, logOdds = FALSE, odds = FALSE, relRisk = FALSE,
  ci = TRUE, ciWidth = 95, compare = "rows",
  hypothesis = "different", gamma = FALSE, taub = FALSE,
  mh = FALSE, obs = TRUE, exp = FALSE, pcRow = FALSE,
  pcCol = FALSE, pcTot = FALSE, barplot = FALSE, yaxis = "ycounts",
  yaxisPc = "total_pc", xaxis = "xrows", bartype = "dodge", 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)
`layers`	the variables to use to split 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
`zProp`	`TRUE` or `FALSE` (default), provide a z test for differences between two proportions
`likeRat`	`TRUE` or `FALSE` (default), provide the likelihood ratio
`fisher`	`TRUE` or `FALSE` (default), provide Fisher's exact test
`contCoef`	`TRUE` or `FALSE` (default), provide the contingency coefficient
`phiCra`	`TRUE` or `FALSE` (default), provide Phi and Cramer's V
`diffProp`	`TRUE` or `FALSE` (default), provide the differences in proportions (only available for 2x2 tables)
`logOdds`	`TRUE` or `FALSE` (default), provide the log odds ratio (only available for 2x2 tables)
`odds`	`TRUE` or `FALSE` (default), provide the odds ratio (only available for 2x2 tables)
`relRisk`	`TRUE` or `FALSE` (default), provide the relative risk (only available for 2x2 tables)
`ci`	`TRUE` or `FALSE` (default), provide confidence intervals for the comparative measures
`ciWidth`	a number between 50 and 99.9 (default: 95), width of the confidence intervals to provide
`compare`	`columns` or `rows` (default), compare columns/rows in difference of proportions or relative risks (2x2 tables)
`hypothesis`	`'different'` (default), `'oneGreater'` or `'twoGreater'`, the alternative hypothesis; group 1 different to group 2, group 1 greater than group 2, and group 2 greater than group 1 respectively
`gamma`	`TRUE` or `FALSE` (default), provide gamma
`taub`	`TRUE` or `FALSE` (default), provide Kendall's tau-b
`mh`	`TRUE` or `FALSE` (default), provide Mantel-Haenszel test for trend
`obs`	`TRUE` or `FALSE` (default), provide the observed counts
`exp`	`TRUE` or `FALSE` (default), provide the expected counts
`pcRow`	`TRUE` or `FALSE` (default), provide row percentages
`pcCol`	`TRUE` or `FALSE` (default), provide column percentages
`pcTot`	`TRUE` or `FALSE` (default), provide total percentages
`barplot`	`TRUE` or `FALSE` (default), show barplots
`yaxis`	ycounts (default) or ypc. Use respectively `counts` or `percentages` for the bar plot y-axis
`yaxisPc`	total_pc (default), column_pc, or row_pc. Use respectively percentages `of total`, `within columns`, or `within rows` for the bar plot y-axis.
`xaxis`	rows (default), or columns in bar plot X axis
`bartype`	stack or side by side (default), barplot type
`formula`	(optional) the formula to use, see the examples

Value

A results object containing:

`results$freqs`					a table of proportions
`results$chiSq`					a table of X² test results
`results$odds`					a table of comparative measures
`results$nom`					a table of the 'nominal' test results
`results$gamma`					a table of the gamma test results
`results$taub`					a table of the Kendall's tau-b test results
`results$mh`					a table of the Mantel-Haenszel test for trend
`results$barplot`					an image

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

results$freqs$asDF

as.data.frame(results$freqs)

Examples

data('HairEyeColor')
dat <- as.data.frame(HairEyeColor)

contTables(formula = Freq ~ Hair:Eye, dat)

#
#  CONTINGENCY TABLES
#
#  Contingency Tables
#  -----------------------------------------------------
#    Hair     Brown    Blue    Hazel    Green    Total
#  -----------------------------------------------------
#    Black       68      20       15        5      108
#    Brown      119      84       54       29      286
#    Red         26      17       14       14       71
#    Blond        7      94       10       16      127
#    Total      220     215       93       64      592
#  -----------------------------------------------------
#
#
#  X² Tests
#  -------------------------------
#          Value    df    p
#  -------------------------------
#    X²      138     9    < .001
#    N       592
#  -------------------------------
#

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

contTables(formula = ~ Hair:Eye, dat)

jmv documentation built on June 22, 2024, 10:40 a.m.