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Management and Business

Join us for a talk with Alan Agresti, Professor Emeritus at University of Florida, Distinguished Author

April 8, 2022 at 11:00am12:00pm EDT

Virtual (See event details)

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Professor Alan Agresti is one of the foremost authors on Categorical Data Analysis and will be giving a short talk on the material from his latest book, Foundations of Statistics for Data Scientists. His abstract for the material “Simple Ways to Interpret Effects in Modeling Binary and Ordinal Data” can be found below.

April 8, 2022

11:00 a.m. – 12:00 p.m. Virtual

Simple Ways to Interpret Effects in Modeling Binary and Ordinal Data


Probability-based effect measures for models for binary and ordinal response variables can be simpler to interpret than logistic (and

probit) regression model parameters and their corresponding effect measures, such as odds ratios. For describing the effect of an

explanatory variable while adjusting for others in modeling a binary response, it is sometimes possible to employ the identity and log link functions to generate simple effect measures. When such link functions are inappropriate, one can still construct analogous effect measures from a logistic regression model fit, based on average differences or ratios of the probability modeled or on average instantaneous rates of change for the probability. Simple measures are also proposed for interpreting effects in models for ordinal responses based on applying a link function to cumulative probabilities. The measures are also sometimes applicable with nonlinear predictors, such as in generalized additive models. The methods are illustrated with examples and implemented with R software.

Parts of this work are joint with Claudia Tarantola and Roberta Varriale.


Alan Agresti, Professor Emeritus at University of Florida, Distinguished Author

Alan Agresti earned his bachelor’s degree in mathematics from the University of Rochester in 1968. He earned his doctorate in statistics from the University of Wisconsin–Madison in 1972.

He was a professor of statistics for many years at the University of Florida, from 1972 until his retirement in 2010 as a Distinguished Professor. He was also a visiting professor at the department of statistics at Harvard University for several years.

He wrote the seminal textbook Categorical Data Analysis during a sabbatical year at Imperial College and has continued to update this work. Dr. Agresti has taught short courses about categorical data analysis for 30 years at universities around the world, including at several Italian universities, and in 2017 became a dual citizen of Italy and the United States.

His most recent publication, Foundations of Statistics for Data Scientists is intended to be a bridge to the essential knowledge of mathematical statistics for data scientists so that they are analyzing data accurately and ethically.

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This event was first published on March 28, 2022 and last updated on April 6, 2022.

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