MarginalHomogeneityTest {coin} | R Documentation |
Testing marginal homogeneity in a complete block design.
## 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"), ...)
formula |
a formula of the form |
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 |
distribution |
a character, the null distribution of the test statistic
can be approximated by its asymptotic distribution ( |
... |
further arguments to be passed to or from methods. |
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. For larger tables, Stuart's W_0
statistic (Stuart, 1955, Agresti, 2002, page 422, also known as Stuart-Maxwell test)
is computed. The marginal homogeneity
statistic W of Bhapkar (1966) can be derived from W_0
via W = W_0 / (1 - W_0 / n) (see Agresti, 2002, page 422).
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).
Note that for a large number of observations, this function is rather inefficient.
An object inheriting from class IndependenceTest
with
methods show
, pvalue
and statistic
.
Alan Agresti (2002). Categorical Data Analysis. Hoboken, New Jersey: John Wiley & Sons.
V. P. Bhapkar (1966). A note on the equivalence of two test criteria for hypotheses in categorical data. Journal of the American Statistical Association 61, 228–235.
Alan Stuart (1955). A test for homogeneity of the marginal distributions in a two-way classification. Biometrika 42(3/4), 412–416.
### 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))) ### example taken from ### http://ourworld.compuserve.com/homepages/jsuebersax/mcnemar.htm rating <- c("low", "moderate", "high") x <- as.table(matrix(c(20, 10, 5, 3, 30, 15, 0, 5, 40), ncol = 3, byrow = TRUE, dimnames = list(Rater1 = rating, Rater2 = rating))) ### test statistic W_0 = 13.76 mh_test(x)