Stuart-Maxwell Marginal Homogeneity Test
This function computes the marginal homogeneity test for a k x k matrix of assignments of objects to k categories or an n x 2 matrix of category scores for n data objects by two raters. The statistic is distributed as chi-square with k-1 degrees of freedom.
It can be viewed as an extention of McNemar test to k x k table.
StuartMaxwellTest(x, y = NULL)
x |
either a 2-way contingency table in matrix form, or a factor object. |
y |
a factor object; ignored if x is a matrix. |
The null is that the probabilities of being classified into cells [i,j] and [j,i] are the same.
If x is a matrix, it is taken as a two-dimensional contingency table, and hence its entries should be nonnegative integers. Otherwise, both x and y must be vectors or factors of the same length. Incomplete cases are removed, vectors are coerced into factors, and the contingency table is computed from these.
A list with class "htest" containing the following components:
statistic |
the value of the test statistic. |
parameter |
the degrees of freedom. |
p.value |
the p-value of the test. |
method |
a character string indicating what type of test was performed. |
data.name |
a character string giving the name of the data. |
Andri Signorell <andri@signorell.net>, based on Code from Jim Lemon
Agresti, A. (2002) Categorical Data Analysis. John Wiley & Sons, pp 86 ff.
hyp <- as.table(matrix(c(20,3,0,10,30,5,5,15,40), nrow=3))
StuartMaxwellTest(hyp)
# Source: http://www.john-uebersax.com/stat/mcnemar.htm#stuart
mc <- as.table(matrix(c(
732, 1524, 1575, 1577, 1602, 837, 1554, 1437,
1672, 1600, 841, 1363, 1385, 1484, 1524, 791), nrow=4))
StuartMaxwellTest(mc)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.