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Dichotomization and Proportional Odds Model (Episode 10)
Manage episode 378107581 series 3515392
Content provided by Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
In this episode, we move from the logistic regression model to proportional odds model, with emphasis on interpretation and the checking of assumptions (visually and analytically). We also speak about the opportunities and challenges of dealing with the dichotomization of ordinal or continuous variables.
Resources:
● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.
● Agresti, Alan. Categorical data analysis. John Wiley & Sons, 2003.
● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)
24 episodes
Share
Manage episode 378107581 series 3515392
Content provided by Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
In this episode, we move from the logistic regression model to proportional odds model, with emphasis on interpretation and the checking of assumptions (visually and analytically). We also speak about the opportunities and challenges of dealing with the dichotomization of ordinal or continuous variables.
Resources:
● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.
● Agresti, Alan. Categorical data analysis. John Wiley & Sons, 2003.
● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)
24 episodes
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Similar to The Effective Data Scientist
The Science Show gives Australians unique insights into the latest scientific research and debate, from the physics of cricket to prime ministerial biorhythms.
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Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
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Whether the topic is popcorn or particle physics, you can count on BrainStuff to explore -- and explain -- the everyday science in the world around us.
…
continue reading
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…
continue reading
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…
continue reading
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…
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