Search Results for: contingency table

We now describe how to estimate the tetrachoric correlation coefficient, i.e. the polychoric correlation coefficient for 2 × 2 contingency tables. In what follows we assume that the contingency table has 2 rows and 2 columns where the element in the ith row and jth column is aij. Method 1 An estimate for the tetrachoric … Read More

Objective Suppose we have a contingency table with m rows and n columns. Further, suppose that the element in the ith row and jth column is aij. Our goal now is to find the value of ρ which maximizes the log-likelihood function LL where We can accomplish this by using Excel’s Solver. Example Example 1: Calculate … Read More

Introduction When data is organized in the form of a contingency table (see Independence Testing) where the two categorical independent variables (corresponding to the row and columns) are ordered, then we can calculate a polychoric correlation coefficient. This coefficient is an approximation to what Pearson’s correlation coefficient would be if we had continuous data. For … Read More

When data is organized in the form of a contingency table where the two categorical independent variables (corresponding to the row and columns) are ordered, then we can calculate a polychoric correlation coefficient. This coefficient is an approximation to what the Pearson’s correlation coefficient would be if we had continuous data. For a 2 × … Read More

Introduction We now show how to perform post-hoc testing using Tukey’s HSD for two-factor ANOVA. This means that we will assume that we are dealing with a balanced model. As described in Tukey HSD for One-way ANOVA (see Unplanned Comparisons) two means are significantly different if where the critical values qcrit are presented in the Studentized Range q Table based … Read More

Basic Concepts The same approach used to calculate a confidence interval for the effect size of a t test (see Confidence Intervals for Power and Effect Size of t Test) can be employed to create a confidence interval for a noncentrality parameter, and in turn Cohen’s effect size and statistical power, for a chi-square goodness … Read More

Introduction For completeness, we now present another non-parametric replacement for one-way ANOVA, namely Mood’s Median Test. This test is essentially an extension of the Sign Test to two or more variables. We have already described this test for two independent variables in Mood’s Median Test for Two Samples. The Kruskal-Wallis test has more power and … Read More