MarginalHomogeneityTest {coin}R Documentation

Marginal Homogeneity Test

Description

Testing marginal homogeneity in a complete block design.

Usage

## S3 method for class 'formula':
mh_test(formula, data, subset = NULL, ...)
## S3 method for class 'table':
mh_test(object, ...)
## S3 method for class 'SymmetryProblem':
mh_test(object, distribution = c("asymptotic", "approximate"), ...) 

Arguments

formula a formula of the form y ~ x | block where y is a factor giving the data values and x a factor with two or more levels giving the corresponding replications. block is an optional factor (which is generated automatically when omitted).
data an optional data frame containing the variables in the model formula.
subset an optional vector specifying a subset of observations to be used.
object an object inheriting from class SymmetryProblem or a table with identical dimnames attributes.
distribution a character, the null distribution of the test statistic can be approximated by its asymptotic distribution (asymptotic) or via Monte-Carlo resampling (approximate). Alternatively, the functions approximate or asymptotic can be used to specify how the exact conditional distribution of the test statistic should be calculated or approximated.
... further arguments to be passed to or from methods.

Details

The null hypothesis of independence of row and column totals is tested. The corresponding test for binary factors x and y is known as McNemar test.

Scores must be a list of length one (row and column scores coincide). When scores are given or if x is ordered, the corresponding linear association test is computed (see Agresti, 2002).

Value

An object inheriting from class IndependenceTest with methods show, pvalue and statistic.

References

Alan Agresti (2002), Categorical Data Analysis. Hoboken, New Jersey: John Wiley & Sons.

Examples


### Opinions on Pre- and Extramarital Sex, Agresti (2002), page 421
opinions <- c("always wrong", "almost always wrong", 
              "wrong only sometimes", "not wrong at all")

PreExSex <- as.table(matrix(c(144, 33, 84, 126, 
                                2,  4, 14,  29, 
                                0,  2,  6,  25, 
                                0,  0,  1,  5), nrow = 4, 
                            dimnames = list(PremaritalSex = opinions,
                                            ExtramaritalSex = opinions)))

### treating response as nominal
mh_test(PreExSex)

### and as ordinal
mh_test(PreExSex, scores = list(response = 1:length(opinions)))


[Package coin version 0.4-7 Index]