Two-Part Predictors in Regression Models

John J. Dziak, Kimberly L. Henry

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Researchers often build regression models to relate a response to a set of predictor variables. In some cases, there are predictors that apply to some participants, or to some measurement occasions, but not others. For example, a romantic partner's substance use may be a key predictor of one's own substance use. However, not all participants have a partner, and in a longitudinal study, participants may have a partner during only some occasions. This could be viewed as missing data, but of a very distinctive type: the values are not just unknown but also undefined. In this paper, we present a simple method to accommodate this situation, along with a motivating example, the algebraic justification, a simulation study, and examples on how to carry out the technique.

Original languageEnglish (US)
Pages (from-to)551-561
Number of pages11
JournalMultivariate Behavioral Research
Issue number5
StatePublished - Sep 3 2017

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)


Dive into the research topics of 'Two-Part Predictors in Regression Models'. Together they form a unique fingerprint.

Cite this