[Forum SIS] Seminar: Alan Agresti - 13 April 2021 (Statistics Seminar @ Ca' Foscari)

[Ilaria Prosdocimi]

Dear all,

The Statistics group at Ca' Foscari University of Venice presents the
following seminar:

Speaker: Alan Agresti (University of Florida)
Title: Simple Ways to Interpret Effects in Modeling Binary and Ordinal Data

13 April 2021 - 14:00 (CET - Rome) - Zoom meeting
https://unive.zoom.us/j/82776377762
Meeting ID: 827 7637 7762 - Passcode: SanMarco1

Abstract:
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 Maria Kateri, Claudia Tarantola, and
Roberta Varriale.

Everybody is welcome to join.

For information on future seminars at Ca' Foscari, see
https://www.unive.it/pag/16818

Best wishes

Ilaria

----
Ilaria Prosdocimi
Assistant Professor in Statistics
Ca' Foscari University of Venice
Department of Environmental Sciences, Informatics and Statistic
prosdocimi.ilaria a gmail.com
ilaria.prosdocimi a unive.it
-------------- parte successiva --------------
Un allegato HTML è stato rimosso...
URL: <http://www.stat.unipg.it/pipermail/sis/attachments/20210407/8b6a737d/attachment.html>