R: Mantel-Haenszel Chi-Square Test

MHChisqTest {DescTools} | R Documentation

## Mantel-Haenszel Chi-Square Test

### Description

The Mantel-Haenszel chi-square statistic tests the alternative hypothesis that there is a linear association between the row variable and the column variable. Both variables must lie on an ordinal scale.

### Usage

    MHChisqTest(x, srow = 1:nrow(x), scol = 1:ncol(x))

### Arguments

`x` | a frequency table or a matrix.
`srow` | scores for the row variable, defaults to 1:nrow.
`scol` | scores for the colummn variable, defaults to 1:ncol.

### Details

The statistic is computed as Q_{MH} = (n-1) \cdot r^2, where r^2 is the Pearson correlation between the row variable and the column variable. The Mantel-Haenszel chi-square statistic use the scores specified by srow and scol. Under the null hypothesis of no association, Q_{MH} has an asymptotic chi-square distribution with one degree of freedom.

### Value

A list with class `"htest"` containing the following components:

`statistic` | the value the Mantel-Haenszel chi-squared test statistic.
`parameter` | the degrees of freedom of the approximate chi-squared distribution of the test statistic.
`p.value` | the p-value for the test.
`method` | a character string indicating the type of test performed.
`data.name` | a character string giving the name(s) of the data.

### Author(s)

Andri Signorell <andri@signorell.net>

### References

Agresti, A. (2002) Categorical Data Analysis. John Wiley & Sons, pp 86 ff.

### See Also

`chisq.test`, for calculating correlation of a table: `corr`

### Examples

    ## A r x c table  Agresti (2002, p. 57) Job Satisfaction
    Job <- matrix(c(1,2,1,0, 3,3,6,1, 10,10,14,9, 6,7,12,11), 4, 4,
                  dimnames = list(income = c("< 15k", "15-25k", "25-40k", "> 40k"),
                                  satisfaction = c("VeryD", "LittleD", "ModerateS", "VeryS"))
           )

    MHChisqTest(Job, srow=c(7.5,20,32.5,60))

[Package DescTools version 0.99.25 Index]