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.
contTables( data, rows, cols, counts = NULL, layers = NULL, chiSq = TRUE, chiSqCorr = FALSE, likeRat = FALSE, fisher = FALSE, contCoef = FALSE, phiCra = FALSE, logOdds = FALSE, odds = FALSE, relRisk = FALSE, ci = TRUE, ciWidth = 95, gamma = FALSE, taub = FALSE, obs = TRUE, exp = FALSE, pcRow = FALSE, pcCol = FALSE, pcTot = FALSE, formula )
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 |
|
chiSqCorr |
|
likeRat |
|
fisher |
|
contCoef |
|
phiCra |
|
logOdds |
|
odds |
|
relRisk |
|
ci |
|
ciWidth | a number between 50 and 99.9 (default: 95), width of the confidence intervals to provide |
gamma |
|
taub |
|
obs |
|
exp |
|
pcRow |
|
pcCol |
|
pcTot |
|
formula | (optional) the formula to use, see the examples |
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 |
Tables can be converted to data frames with asDF
or as.data.frame
. For example:
results$freqs$asDF
if (FALSE) { # 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) }