Reversal.Association.Finder: Given an input matrix, we can split it into smaller...

In RajeswaranV/vcdPlus: Summary and inference of categorical data and contingency tables

Description

Given an input matrix, we can split it into smaller sub-matrix (min 2x2) and then find the Chi-squared test for each sub-matrix. The smaller matrix can "support" or "oppose" (have a different conclusion at 95 test value of the full input matrix. We count the number of times each cell supports or opposes the overall Chi-squared test. We also generate the possible list of sub-matrix.

Usage

Reversal.Association.Finder(mat)

Arguments

mat	- matrix for which the sub-matrix is to be generated

Details

This can be used as an outlier detection method as well as observing the individual cells within an IxJ table

Value

A dataframe with

Dimention.row	Number of rows
Dimention.col	Number of columns
Chi-sq-test.value	Chi squared test value
Significance at .95	Test for significance at .95 confidence level

References

[1] J.Berkson Some difficulties of interpretation encountered in the application of the chi-square test Journal of the American Statistical Association. 33, 1938, 526-536. [2] H.W,Norton Calculation of chi-square for complex contingency tables Journal of the American Statistical Association. 40, 1945, 251-258. [3] C.R. Blyth On Simpsons paradox and the sure thing principle. Journal of the American Statistical Association. 67, 1972, 364-366. [4] A.Agresti Categorical Data Analysis (New York: Wiley & Sons 1990) pp 51-54.

Examples

## Most influential school of Psychiatric thought and ascribed origin of schizophrenia- Agresti 1992
Eclectic=c(90,	12,	78) # Example from [reference 4]
Medical=c(13,	1,	6)
Psychoanalytic=c(19,	13,	50)
mat=rbind(Eclectic,Medical,Psychoanalytic)
Reversal.Association.Finder(mat)

RajeswaranV/vcdPlus documentation built on May 27, 2019, 7:28 a.m.