Search Results for: contingency table

Introduction Goodman and Kruskal’s Gamma Test is described in Gamma Measure of Association. Here we show how perform the Bayesian version of this non-parametric test in Excel.  Essentially this entails using the Bayesian version of Kendall’s tau test. Example Example 1: Repeat Example 1 of Gamma Measure of Association using a Bayesian approach (the data is … Read More

Objective We describe worksheet functions and data analysis tools that can be used to perform Bayesian independence testing in Excel. These capabilities implement the approach described in Bayesian Independence Testing and are provided by the Real Statistics Resource Pack. Worksheet Functions The Real Statistics Resource Pack provides the following worksheet array function in support of … Read More

Objective We describe the Bayesian approach to determining whether the two variables defined by a contingency table are independent. This is the Bayesian equivalence to the chi-square test of independence or Fisher’s exact test. See also Bayesian Hypothesis Testing. Terminology We assume that we have an m × n contingency table X = [xij] and … Read More

Basic Concepts Somers’ d statistic is a measure of (asymmetric) association. d takes values between -1 and 1. A value of 1 or -1 means that the independent variable perfectly predicts the dependent variable: +1 when the relationship is positive and -1 when the relationship is negative. A value of 0 means that there is … Read More

Basic Concepts The lambda coefficient is a measure of (asymmetric) association that reflects the proportional reduction in error (PRE) when values of the independent variable are used to predict values of the dependent variable. Lambda takes values between 0 and 1. A value of 1 means that the independent variable perfectly predicts the dependent variable. … Read More

Basic Concepts Goodman and Kruskal’s gamma statistic is a measure of (symmetric) association between two ordinal variables. Gamma takes values between -1 and 1. A value of 1 or -1 means that the variables have a perfect association: +1 when the relationship is positive and -1 when the relationship is negative. A value of 0 … Read More