Graphics for studying logistic regression models
Luca Scrucca
Statistical Methods & Applications, 2002, vol. 11, issue 3, No 7, 394 pages
Abstract:
Abstract In this article we focus on logistic regression models for binary responses. An existing result shows that the log-odds can be modelled depending on the log of the ratio between the conditional densities of the predictors given the response variable. This suggests that relevant statistical information could be extracted investigating the inverse problem. Thus, we present different methods for studying the log-density ratio through graphs, which allow us to select which predictors are needed, and how they should be included in a logistic regression model. We also discuss data analysis examples based on real datasets available in literature in order to provide further insights into the methodology proposed.
Keywords: Logistic regression; binary response; log-density ratio; regression graphics; kernel density estimate; conditional QQ-plot; local likelihood (search for similar items in EconPapers)
Date: 2002
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/BF02509833 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:stmapp:v:11:y:2002:i:3:d:10.1007_bf02509833
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2
DOI: 10.1007/BF02509833
Access Statistics for this article
Statistical Methods & Applications is currently edited by Tommaso Proietti
More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().