Logistic on It was simple
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Recent content in Logistic on It was simpleHugo -- gohugo.ioHansjörg PlieningerMon, 13 May 2019 00:00:00 +0000Regression Modeling With Proportion Data (Part 2)
https://hansjoerg.me/2019/05/13/regression-modeling-with-proportion-data-part-2/
Mon, 13 May 2019 00:00:00 +0000https://hansjoerg.me/2019/05/13/regression-modeling-with-proportion-data-part-2/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).Regression Modeling With Proportion Data (Part 1)
https://hansjoerg.me/2019/05/10/regression-modeling-with-proportion-data-part-1/
Fri, 10 May 2019 00:00:00 +0000https://hansjoerg.me/2019/05/10/regression-modeling-with-proportion-data-part-1/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.