scrime (version 1.2.9)

rowChisq2Class: Rowwise Pearson's ChiSquare Test Based on Tables

Description

Given a set of matrices, each of which represents one group of subjects, and summarizes rowwise the numbers of these observations showing the levels of the categorical variables represented by the rows of the matrices, the value of Pearson's ChiSquare statistic for testing whether the distribution of the variable differs between the different groups is computed for each variable. Using this function instead of rowChisqStats is recommended when the total number of observations is very large.

Usage

rowChisq2Class(cases, controls, add.pval = TRUE, sameNull = FALSE)

rowChisqMultiClass(..., listTables = NULL, add.pval = TRUE,
   sameNull = FALSE)

Arguments

cases

a numeric matrix in which each row represents one categorical variable and each column one of the levels that the variables exhibit. The entries of this matrix are the numbers of observations from one group (e.g., the cases in a case-con

controls

a numeric matrix of the same dimensions as cases comprising the numbers of observations from the second group (e.g., the controls in a case-control study) that show the respective level at the different variables. The rows o

...

numeric matrices (such as cases and controls) each of which comprises the numbers of observations showing the respective levels at the different variables. The dimensions of all matrices must be the same, and the rows

listTables

instead of inputting the matrices directly into rowChisqMultiClass a list can generated, where each entry of this list is one of matrices, and this list can be used in rowChisqMultiClass by specifying listTables

add.pval

should p-values be added to the output? If FALSE, only the rowwise values of Pearson's ChiSquare statistic will be returned. If TRUE, additionally the degrees of freedom and the (raw) p-values are computed by assuming

sameNull

should all variables follow the same null distribution? If TRUE, then all variables must show the same number of levels such that their null distribution is approximated by the same ChiSquare-distribution.

Value

• Either a vector containing the rowwise values of Pearson's ChiSquare statistic (if add.pval = FALSE) or a list containing these values (stats), the degrees of freedom (df), and the p-values (rawp) not adjusted for multiple comparisons (if add.pval = TRUE).

See Also

rowChisqStats, rowTables, rowCATTs, rowMsquares

Examples

# Generate a matrix containing data for 10 categorical 
# variables with levels 1, 2, 3.

mat <- matrix(sample(3, 500, TRUE), 10)

# Now assume that the first 25 columns correspond to
# cases and the remaining 25 columns to cases. Then
# a vector containing the class labels is given by

cl <- rep(1:2, e=25)

# and the matrices summarizing the numbers of subjects
# showing the respective levels at the different variables
# are computed by

cases <- rowTables(mat[, cl==1])
controls <- rowTables(mat[,cl==2])

# To obtain the ChiSquare values call

rowChisq2Class(cases, controls)

# This leads to the same results as

rowChisqStats(mat, cl)

# or

rowChisqMultiClass(cases, controls)

# or

listTab <- list(cases, controls)
rowChisqMultiClass(listTables = listTab)