5.4.5 - Other Calculated Measures of Association - Teradata Warehouse Miner
Teradata Warehouse Miner User Guide - Volume 3Analytic Functions
- Teradata Warehouse Miner
- Release Number
- February 2018
- English (United States)
- Last Update
Phi coefficient — The Phi coefficient is a measure of the degree of association between two binary variables, and represents the correlation between two dichotomous variables. It is based on adjusting chi-square significance to factor out sample size, and is the same as the Pearson correlation for two dichotomous variables.
Cramer’s V — Cramer's V is used to examine the association between two categorical variables when there is more than a 2 X 2 contingency (e.g., 2 X 3). In these more complex designs, phi is not appropriate, but Cramer's statistic is. Cramer's V represents the association or correlation between two variables. Cramer's V is the most popular of the chi-square-based measures of nominal association, designed so that the attainable upper limit is always 1.
Likelihood Ratio Chi Square — Likelihood ratio chi-square is an alternative to test the hypothesis of no association of columns and rows in nominal-level tabular data. It is based on maximum likelihood estimation, and involves the ratio between the observed and the expected frequencies, whereas the ordinary chi-square test involves the difference between the two. This is a more recent version of chi-square and is directly related to log-linear analysis and logistic regression.
Continuity-Adjusted Chi-Square — The continuity-adjusted chi-square statistic for 2 × 2 tables is similar to the Pearson chi-square, except that it is adjusted for the continuity of the chi-square distribution. The continuity-adjusted chi-square is most useful for small sample sizes. The use of the continuity adjustment is controversial; this chi-square test is more conservative, and more like Fisher's exact test, when your sample size is small. As the sample size increases, the statistic becomes more and more like the Pearson chi-square.
Contingency Coefficient — The contingency coefficient is an adjustment to phi coefficient, intended for tables larger than 2-by-2. It is always less than 1 and approaches 1.0 only for large tables. The larger the contingency coefficient, the stronger the association. Recommended only for 5-by-5 tables or larger, for smaller tables it underestimates level of association.