# ADA: Average Deviation Analog (ADA) In qualvar: Implements Indices of Qualitative Variation Proposed by Wilcox (1973)

## Description

Computes the average deviation analog (ADA) for a vector of frequencies of categories.

## Usage

 1 ADA(x, na.rm = TRUE) 

## Arguments

 x a vector of frequencies na.rm if TRUE, missing values are removed. If FALSE, NA is returned if there is any NA value.

## Details

According to Wilcox (1973, p. 328), the ADA is 'an analog of the average or mean deviation'. The formula for the ADA is:

1 - \frac{∑_{i=1}^k ≤ft| f_i - \frac{N}{K}\right|}{2 \frac{N}{K}(K-1)}

## Value

The value of the ADA statistics, which is normalised (varies between 0 and 1).

## References

Wilcox, Allen R. 'Indices of Qualitative Variation and Political Measurement.' The Western Political Quarterly 26, no. 2 (1 June 1973): 325-43. doi:10.2307/446831.

## Examples

 1 2 3 4 5 6 7 x <- rmultinom(1, 100, rep_len(0.25, 4)) x <- as.vector(t(x)) ADA(x) df <- rmultinom(10, 100, rep_len(0.25, 4)) df <- as.data.frame(t(df)) apply(df, 1, ADA) 

qualvar documentation built on May 2, 2019, 1:14 a.m.