Consider a data set where each observation involves counting the number of successes from an observed number of trials. A logistic regression model is fitted and we find that its deviance is too large, indicating lack-of-fit. Which of the followings are possible remedies? O Including additional explanatory terms in the model. O Taking the square root of the deviance to make it smaller. O Checking whether the included explanatory terms need transformations. O Fitting a Poisson regression model to the data instead. O Log-transforming the response (the number of successful trials) and refit the logistic regression model.
Consider a data set where each observation involves counting the number of successes from an observed number of trials. A logistic regression model is fitted and we find that its deviance is too large, indicating lack-of-fit. Which of the followings are possible remedies? O Including additional explanatory terms in the model. O Taking the square root of the deviance to make it smaller. O Checking whether the included explanatory terms need transformations. O Fitting a Poisson regression model to the data instead. O Log-transforming the response (the number of successful trials) and refit the logistic regression model.
Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.3: Modeling Data With Power Functions
Problem 3TU
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Transcribed Image Text:Consider a data set where each observation involves counting the number of successes from an
observed number of trials. A logistic regression model is fitted and we find that its deviance is too
large, indicating lack-of-fit.
Which of the followings are possible remedies?
Including additional explanatory terms in the model.
Taking the square root of the deviance to make it smaller.
Checking whether the included explanatory terms need transformations.
Fitting a Poisson regression model to the data instead.
Log-transformíng the response (the number of successful trials) and refit the logistic regression model.
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