LehmacherTest.Rd
Performs Lehmacher's chi-squared test for marginal homogenity in a symmetric two-dimensional contingency table.
LehmacherTest(x, y = NULL)
# S3 method for class 'mtest'
print(x, digits = 4L, ...)
either a two-dimensional contingency table in matrix form, or a factor object.
a factor object; ignored if x is a matrix.
a non-null value for digits specifies the minimum number of significant digits to be printed in values. See details in print.default
.
further arguments to be passed to or from other methods. They are ignored in this function.
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 "mtest"
containing the following components:
a vector with the value of the test statistics.
the degrees of freedom, which is always 1 in LehmacherTest.
a vector with the p-values of the single tests.
a vector with the "hochberg" adjusted p-values of the single tests. (See p.adjust
)
a character string indicating what type of test was performed.
a character string giving the name of the data.
Lehmacher, W. (1980) Simultaneous sign tests for marginal homogeneity of square contingency tables Biometrical Journal, Volume 22, Issue 8, pages 795-798
mcnemar.test
(resp. BowkerTest for a CxC-matrix), StuartMaxwellTest
, WoolfTest
x <- matrix(c(400,40,20,10,
50,300,60,20,
10,40,120,5,
5,90,50,80), nrow=4, byrow=TRUE)
LehmacherTest(x)
#>
#> Lehmacher-Test on Marginal Homogeneity
#>
#> data: x
#> X-squared pval pval adj
#> 1 0.1852 0.66695 0.66695
#> 2 5.3333 0.02092 0.04184 *
#> 3 30.4054 3.505e-08 1.052e-07 ***
#> 4 67.2222 2.220e-16 8.882e-16 ***
#>
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>