betaByGroup: Estimate Beta-Binomial Parameters by Group

In WLenhard/cNORM: Continuous Norming

Estimate Beta-Binomial Parameters by Group

Description

This function calculates the beta-binomial distribution parameters (alpha, beta, mean, variance) for subsets of data grouped by a specified factor. It applies the 'betaCoefficients' function to each group separately, aggregating the results into a single data frame. This is particularly useful for analyzing heterogeneity in success probabilities across different groups within a dataset.

Usage

betaByGroup(x, group, n)

Arguments

x	A vector of non-negative integers representing the number of successes in trials for the entire dataset.
group	A factor or similar object that divides 'x' into groups. Each element of 'x' is associated with a group indicated by the corresponding element in 'group'.
n	The maximum number of trials, assumed to be the same for all groups.

Details

The function first identifies unique groups in the 'group' argument and then iterates over these groups. For each group, it extracts the subset of 'x' corresponding to that group and computes the beta-binomial distribution parameters using the 'betaCoefficients' function. The results are compiled into a matrix that is then converted into a data frame for easier manipulation and interpretation.

Value

A data frame where each row contains the beta-binomial distribution parameters (alpha 'a', beta 'b', mean 'm', variance 'var') for a group, along with the group identifier. The columns are named 'a', 'b', 'm', 'var', 'n', and 'group', with each row corresponding to a distinct group in the input.

Examples

x <- elfe$raw
group <- elfe$group
n <- 26
betaByGroup(x, group, n)

WLenhard/cNORM documentation built on April 1, 2024, 5:41 p.m.