Term: Stepwise Logistic Regression
Last Updated: 2012-05-16
A regression technique used when the outcome is a binary, or dichotomous, variable. Logistic regression models the probability of an event as a function of other factors. Stepwise logistic regression involves the stepwise (or one-by-one) selection of variables, providing a fast and effective method to screen a large number of variables, and to fit multiple logistic regression equations simultaneously. These models are only able to state that there is a relationship ("association") between the explanatory and the outcome variables. This is not necessarily a causal relationship, since it is based on observational data for the most recent time period. The explanatory variable may be associated with an increase or decrease (not that it caused the increase or decrease).
- Hosmer DW, Lemeshow S. Applied Logistic Regression (2nd Edition). New York, NY: John Wiley & Sons; 2000.(View)
- Santos R, Brownell M, Ekuma O, Mayer T, Soodeen R-A. The Early Development Instrument (EDI) in Manitoba: Linking Socioeconomic Adversity and Biological Vulnerability at Birth to Children's Outcomes at Age 5. Winnipeg, MB: Manitoba Centre for Health Policy, 2012. [Report] [Summary] (View)
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