Goodman-Kruskal's gamma statistic for a two-dimensional table

Compute Goodman-Kruskal's gamma statistic for a two-dimensional table of ordered categories

gkgamma(x, conf.level = 0.95)

Arguments

x	A matrix or table representing the two-dimensional ordered contingency table of observations
conf.level	Level of confidence interval

Value

A list with class htest containing the following components:

statistic

the value the test statistic for testing no association

p.value

the p-value for the test

estimate

the value the gamma estimate

conf.int

the confidence interval for the gamma estimate

method

a character string indicating the type of test performed

data.name

a character string indicating the name of the data input

observed

the observed counts

s0

the SE used when computing the test statistics

s1

the SE used when computing the confidence interval

References

Goodman, Leo A. and Kruskal, William H. (1954). "Measures of Association for Cross Classifications". Journal of the American Statistical Association 49 (268): 732-764.

See also

chisq.test

Examples

# Data from the Glostrup study comparing smoking to overall health in males
smoke <- matrix(c(16, 15, 13, 10, 1, 73, 75, 59, 81, 29, 6, 6, 7, 17, 3, 1, 0, 1, 3, 1), ncol=4)
colnames(smoke) <- c("VGood", "Good", "Fair", "Bad") # General health status
rownames(smoke) <- c("Never", "No more", "1-14", "15-24", "25+")  # Smoke amount
gkgamma(smoke)
#> 
#> 	Goodman-Kruskal's gamma for ordinal categorical data
#> 
#> data:  smoke
#> Z = 3.297, p-value = 0.0009771
#> 95 percent confidence interval:
#>  0.1033214 0.3803133
#> sample estimates:
#> Goodman-Kruskal's gamma 
#>               0.2418174 
#> 
chisq.test(smoke)
#> Warning: Chi-squared approximation may be incorrect
#> 
#> 	Pearson's Chi-squared test
#> 
#> data:  smoke
#> X-squared = 16.198, df = 12, p-value = 0.1824
#>