gmodels (version 2.18.1)

# CrossTable: Cross Tabulation with Tests for Factor Independence

## Description

An implementation of a cross-tabulation function with output similar to S-Plus crosstabs() and SAS Proc Freq (or SPSS format) with Chi-square, Fisher and McNemar tests of the independence of all table factors.

## Usage

CrossTable(x, y, digits=3, max.width = 5, expected=FALSE, prop.r=TRUE, prop.c=TRUE,
prop.t=TRUE, prop.chisq=TRUE, chisq = FALSE, fisher=FALSE, mcnemar=FALSE,
resid=FALSE, sresid=FALSE, asresid=FALSE,
missing.include=FALSE,
format=c("SAS","SPSS"), dnn = NULL, ...)

## Arguments

x

A vector or a matrix. If y is specified, x must be a vector

y

A vector in a matrix or a dataframe

digits

Number of digits after the decimal point for cell proportions

max.width

In the case of a 1 x n table, the default will be to print the output horizontally. If the number of columns exceeds max.width, the table will be wrapped for each successive increment of max.width columns. If you want a single column vertical table, set max.width to 1

expected

If TRUE, chisq will be set to TRUE and expected cell counts from the $$\chi^2$$ will be included

prop.r

If TRUE, row proportions will be included

prop.c

If TRUE, column proportions will be included

prop.t

If TRUE, table proportions will be included

prop.chisq

If TRUE, chi-square contribution of each cell will be included

chisq

If TRUE, the results of a chi-square test will be included

fisher

If TRUE, the results of a Fisher Exact test will be included

mcnemar

If TRUE, the results of a McNemar test will be included

resid

If TRUE, residual (Pearson) will be included

sresid

If TRUE, standardized residual will be included

asresid

If TRUE, adjusted standardized residual will be included

missing.include

If TRUE, then remove any unused factor levels

format

Either SAS (default) or SPSS, depending on the type of output desired.

dnn

the names to be given to the dimensions in the result (the dimnames names).

optional arguments

## Value

A list with multiple components including key table data and statistical test results, where performed.

t: An n by m matrix containing table cell counts

prop.col: An n by m matrix containing cell column proportions

prop.row: An n by m matrix containing cell row proportions

prop.tbl: An n by m matrix containing cell table proportions

chisq: Results from the Chi-Square test. A list with class 'htest'. See ?chisq.test for details

chisq.corr: Results from the corrected Chi-Square test. A list with class 'htest'. See ?chisq.test for details. ONLY included in the case of a 2 x 2 table.

fisher.ts: Results from the two-sided Fisher Exact test. A list with class 'htest'. See ?fisher.test for details. ONLY included if 'fisher' = TRUE.

fisher.lt: Results from the Fisher Exact test with HA = "less". A list with class 'htest'. See ?fisher.test for details. ONLY included if 'fisher' = TRUE and in the case of a 2 x 2 table.

fisher.gt: Results from the Fisher Exact test with HA = "greater". A list with class 'htest'. See ?fisher.test for details. ONLY included if 'fisher' = TRUE and in the case of a 2 x 2 table.

mcnemar: Results from the McNemar test. A list with class 'htest'. See ?mcnemar.test for details. ONLY included if 'mcnemar' = TRUE.

mcnemar.corr: Results from the corrected McNemar test. A list with class 'htest'. See ?mcnemar.test for details. ONLY included if 'mcnemar' = TRUE and in the case of a 2 x 2 table.

resid/sresid/asresid: Pearson Residuals (from chi-square tests).

## Details

A summary table will be generated with cell row, column and table proportions and marginal totals and proportions. Expected cell counts can be printed if desired (if 'chisq = TRUE'). In the case of a 2 x 2 table, both corrected and uncorrected values will be included for appropriate tests. In the case of tabulating a single vector, cell counts and table proportions will be printed.

Note: If 'x' is a vector and 'y' is not specified, no statistical tests will be performed, even if any are set to TRUE.

xtabs, table, prop.table

## Examples

# NOT RUN {
# Simple cross tabulation of education versus prior induced abortions
# using infertility data
data(infert, package = "datasets")
CrossTable(infert$education, infert$induced, expected = TRUE)
CrossTable(infert$education, infert$induced, expected = TRUE, format="SAS")
CrossTable(infert$education, infert$induced, expected = TRUE, format="SPSS")
CrossTable(warpbreaks$wool, warpbreaks$tension, dnn = c("Wool", "Tension"))
# }