# Assocs: Association Measures In AndriSignorell/DescTools: Tools for Descriptive Statistics

## Description

Collects a number of association measures for nominal and ordinal data.

## Usage

 ```1 2 3 4``` ```Assocs(x, conf.level = 0.95, verbose = NULL) ## S3 method for class 'Assocs' print(x, digits = 4, ...) ```

## Arguments

 `x` a 2 dimensional contingency table or a matrix. `conf.level` confidence level of the interval. If set to `NA` no confidence interval will be calculated. Default is 0.95. `verbose` integer out of `c(2, 1, 3)` defining the verbosity of the reported results. 2 (default) means medium, 1 less and 3 extensive results. Applies only to tables and is ignored else. `digits` integer which determines the number of digits used in formatting the measures of association. `...` further arguments to be passed to or from methods.

## Details

This function wraps the association measures phi, contingency coefficient, Cramer's V, Goodman Kruskal's Gamma, Kendall's Tau-b, Stuart's Tau-c, Somers' Delta, Pearson and Spearman correlation, Guttman's Lambda, Theil's Uncertainty Coefficient and the mutual information.

## Value

numeric matrix, dimension [1:17, 1:3]
the first column contains the estimate, the second the lower confidence interval, the third the upper one.

## Author(s)

Andri Signorell <andri@signorell.net>

`Phi`, `ContCoef`, `CramerV`, `GoodmanKruskalGamma`, `KendallTauB`, `StuartTauC`, `SomersDelta`, `SpearmanRho`, `Lambda`, `UncertCoef`, `MutInf`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29``` ```options(scipen=8) # Example taken from: SAS/STAT(R) 9.2 User's Guide, Second Edition, The FREQ Procedure # http://support.sas.com/documentation/cdl/en/statugfreq/63124/PDF/default/statugfreq.pdf # Hair-Eye-Color pp. 1816 tob <- as.table(matrix(c( 69, 28, 68, 51, 6, 69, 38, 55, 37, 0, 90, 47, 94, 94, 16 ), nrow=3, byrow=TRUE, dimnames=list(eye=c("blue","green","brown"), hair=c("fair","red","medium","dark","black")) )) Desc(tob) Assocs(tob) # Example taken from: http://www.math.wpi.edu/saspdf/stat/chap28.pdf # pp. 1349 pain <- as.table(matrix(c( 26, 6, 26, 7, 23, 9, 18, 14, 9, 23 ), ncol=2, byrow=TRUE)) Desc(pain) Assocs(pain) ```