Fungible weights in logistic regression

Jeff A. Jones, Niels G. Waller

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights.

Original languageEnglish (US)
Pages (from-to)241-260
Number of pages20
JournalPsychological Methods
Volume21
Issue number2
DOIs
StatePublished - 2016

Keywords

  • Fungible weights
  • Logistic regression
  • Model evaluation
  • Parameter sensitivity

Fingerprint Dive into the research topics of 'Fungible weights in logistic regression'. Together they form a unique fingerprint.

Cite this