Search Results for: contingency table

The chi-square test of independence described in Independence Testing uses categorical data. If the rows and columns in the contingency table are ordered, this ordering is not taken into account. We now show how to take this order into account. Example Example 1: 127 people who attended a training course were asked to rate their … Read More

On this webpage, we describe Real Statistics’ support for chi-square independence testing with missing data. Worksheet Functions Real Statistics Functions: The Real Statistics Resource Pack provides the following array functions. Here R1 is an m+1 × n+1 array, the last row and last column of which contains counts of missing elements. EM_CHISQ(R1, iter, prec): outputs … Read More

Basic Concepts We now show how to conduct the chi-square test for independence even when there is missing data by using the EM approach described in Contingency Tables with Missing Data. If the row and column variables of a contingency table are assumed to be independent, then we can apportion the missing data using an … Read More

The EM algorithm can be used when a data set has missing data elements. The missing data is estimated using an iterative process where each iteration consists of two steps: (1) an M step (maximization) where parameters are calculated based on the missing data results from the previous E step (or via a guess in … Read More

The following is a summary of the Regression and ANOVA worksheet functions provided in the Real Statistics Resource Pack. These functions are organized into the following categories: Linear Regression Heteroskedasticity Autocorrelation Bootstrapping Regression Power and Sample Size Stepwise Regression Exponential Regression Polynomial Regression Least Absolution Deviation (LAD) Regression Deming Regression Total Least Squares Regression Passing-Bablok … Read More

Example Example 1: A study was conducted to see whether there was a difference in the rate of lung cancer between people who smoked one pack of cigarettes a day and those who regularly smoked an electronic cigarette. In the study, the confounding effect of the pollution level in the city where the smoker resided … Read More

The Cochran-Mantel-Haenszel (CMH) test is used to test multiple 2 ⨯ 2 contingency tables across different values of a confounding variable. The test determines whether there is a significant difference between the odds ratios across the different values of the confounding variable. We represent each of the k 2 ⨯ 2 contingency as shown in … Read More

The Cochran-Mantel-Haenszel (CMH) test is used to test multiple 2 × 2 contingency tables across different values of a confounding variable. The test determines whether there is a significant difference between the odds ratios across the different values of the confounding variable. Topics Basic Concepts Example Real Statistics Support Links ↑ Chi-square and F distributions … Read More