Abstract
Probably the most common statistical technique in predictive modeling is the binary response, or logistic regression, model. This model is designed to predict either/or behavior such as “Will the customer buy?” or “Will the customer churn?” We discuss logistic regression and other discrete models such as discriminant analysis, multinomial logit, and count data methods. Duration models, the second part of this chapter, model the timing for an event to occur. One form of duration model, the hazard model, is particularly important because it can be used to predict how long the customer will remain as a current customer. It can also predict how long it will take before the customer decides to make another purchase, switch to an upgrade, etc. We discuss hazard models in depth.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Blattberg, R.C., Kim, BD., Neslin, S.A. (2008). Discrete Dependent Variables and Duration Models. In: Database Marketing. International Series in Quantitative Marketing, vol 18. Springer, New York, NY. https://doi.org/10.1007/978-0-387-72579-6_15
Download citation
DOI: https://doi.org/10.1007/978-0-387-72579-6_15
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-72578-9
Online ISBN: 978-0-387-72579-6
eBook Packages: Business and EconomicsBusiness and Management (R0)