Type: | Package |
Title: | A Post Hoc Analysis for Pearson's Chi-Squared Test for Count Data |
Version: | 0.1.2 |
Description: | Perform post hoc analysis based on residuals of Pearson's Chi-squared Test for Count Data based on T. Mark Beasley & Randall E. Schumacker (1995) <doi:10.1080/00220973.1995.9943797>. |
License: | GPL-3 |
URL: | http://chisq-posthoc-test.ebbert.nrw/ |
BugReports: | https://github.com/ebbertd/chisq.posthoc.test/issues |
Suggests: | knitr, testthat |
VignetteBuilder: | knitr |
Encoding: | UTF-8 |
LazyData: | true |
RoxygenNote: | 6.1.1 |
NeedsCompilation: | no |
Packaged: | 2019-10-21 15:13:48 UTC; ebbertd |
Author: | Daniel Ebbert |
Maintainer: | Daniel Ebbert <daniel.ebbert@uni-muenster.de> |
Repository: | CRAN |
Date/Publication: | 2019-10-25 08:00:06 UTC |
Perform post hoc analysis based on residuals of Pearson's Chi-squared Test for Count Data.
Description
Perform post hoc analysis based on residuals of Pearson's Chi-squared Test for Count Data.
Usage
chisq.posthoc.test(x, method = "bonferroni", round = 6, ...)
Arguments
x |
A matrix passed on to the chisq.test function. |
method |
The p adjustment method to be used. This is passed on to the p.adjust function. |
round |
Number of digits to round the p.value to. Defaults to 6. |
... |
Additional arguments passed on to the chisq.test function. |
Value
A table with the adjusted p value for each x y combination.
References
Agresti, A. (2007). An Introduction to Categorical Data Analysis, 2nd ed. New York: John Wiley & Sons. Page 38.
Beasley, T. M., & Schumacker, R. E. (1995). Multiple Regression Approach to Analyzing Contingency Tables: Post Hoc and Planned Comparison Procedures. The Journal of Experimental Education, 64(1), 79–93.
Examples
# Data from Agresti(2007) p.39
M <- as.table(rbind(c(762, 327, 468), c(484, 239, 477)))
dimnames(M) <- list(gender = c("F", "M"),
party = c("Democrat","Independent", "Republican"))
# Pass data matrix to chisq.posthoc.test function
chisq.posthoc.test(M)