Regression Modeling With Proportion Data (Part 2)

Attendance in Handball-Bundesliga Rose By 7 % After World Championship

Data Analyses: Beta and Quasi-Binomial Regression Results Plot Model Comparison Effect Size In the first part of this post, I demonstrated how beta and quasi-binomial regression can be used with dependent variables that are proportions or ratios. I applied these models to attendance rates of the German Handball-Bundesliga. In the second part, I want to investigate whether attendance increased after the World Championship that took place in January 2019 in Denmark and Germany (with a new spectator record). [Read More]

Regression Modeling With Proportion Data (Part 1)

Predicting Attendance in the German Handball-Bundesliga

Modeling Proportion Data Application: Handball-Bundesliga Setup Selected Variables Initial Results for Beta Regression Illustrative Plot of Estimates Residuals Model Comparisons Models Considered Model Performance Prediction of Future Matches Resources As a data scientist, one often encounters dependent variables that are proportions: for example, the number of successes divided by the number of attempts, party vote, proportion of money spent for something, or the attendance rate of public events. [Read More]

Categorical Predictors in ANOVA and Regression

Regression Perspective ANOVA and SPSS Perspective How to Combine the Perspectives? Solution Examples Example data Dummy Coding Planned Comparisons/Contrast Coding Helmert Coding Orthogonal and Nonorthognoal Contrasts References Data with categorical predictors such as groups, conditions, or countries can be analyzed in a regression framework as well as in an ANOVA framework. In either case, the grouping variable needs to be recoded, it cannot enter the model like a continuous predictor such as age or income. [Read More]