jmv (version 2.7.7)

contTables: 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",
  resU = FALSE, resP = FALSE, hlresP = 2, resS = FALSE,
  hlresS = 2, resA = FALSE, hlresA = 2, formula)

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$mh					a table of the Mantel-Haenszel test for trend
results$postHoc					a table of post-hoc residuals
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)

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

resU

TRUE or FALSE (default), display unstandardized residuals in the post hoc tests table.

resP

TRUE or FALSE (default), display Pearson residuals in the post hoc tests table.

hlresP

A numeric value (default: 2.0), highlight Pearson residuals above this threshold in the post hoc tests table.

resS

TRUE or FALSE (default), display standardized residuals (adjusted Pearson) in the post hoc tests table.

hlresS

A numeric value (default: 2.0), highlight standardized residuals above this threshold in the post hoc tests table.

resA

TRUE or FALSE (default), display deviance residuals from a Poisson GLM in the post hoc tests table.

hlresA

A numeric value (default: 2.0), highlight deviance residuals above this threshold in the post hoc tests table.

formula

(optional) the formula to use, see the examples

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)