ABSTRACT
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.
Article information
Support for the Rochester Youth Development Study has been provided by the Office of Juvenile Justice and Delinquency Prevention (86-JN-CX-0007, 96-MU-FX-0014, and 2004-MU-FX-0062), the National Institute on Drug Abuse (R01DA020195 and R01DA005512), the National Science Foundation (SBR-9123299), and the National Institute of Mental Health (R01MH56486 and R01MH63386). Technical assistance for this project was also provided by an NICHD (Eunice Kennedy Shriver National Institute of Child Health and Human Development) grant (R24HD044943) to The Center for Social and Demographic Analysis at the University at Albany. The research in this paper was also supported by awards P50 DA010075 and P50 DA039838 from the National Institute of Drug Abuse (National Institutes of Health, United States). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions as mentioned above. The authors thank Amanda Applegate for assistance in editing and considerably improving the manuscript. The authors would also like to thank an anonymous reviewer for suggesting the inclusion of , among other important improvements.
Conflict of interest disclosures: Each author signed a form for disclosure of potential conflicts of interest. No authors reported any financial or other conflicts of interest in relation to the work described.
Ethical principles: The authors affirm having followed professional ethical guidelines in preparing this work. These guidelines include obtaining informed consent from human participants, maintaining ethical treatment and respect for the rights of human or animal participants, and ensuring the privacy of participants and their data, such as ensuring that individual participants cannot be identified in reported results or from publicly available original or archival data.
Funding: This work was supported by awards P50 DA010075 and P50 DA039838 from the National Institute of Drug Abuse (National Institutes of Health, United States). Support for the Rochester Youth Development Study has been provided by the Office of Juvenile Justice and Delinquency Prevention (86-JN-CX-0007, 96-MU-FX-0014, and 2004-MU-FX-0062), the National Institute on Drug Abuse (R01DA020195 and R01DA005512), the National Science Foundation (SBR-9123299), and the National Institute of Mental Health (R01MH56486, R01MH63386). Technical assistance for this project was also provided by an NICHD (Eunice Kennedy Shriver National Institute of Child Health and Human Development) grant (R24HD044943) to The Center for Social and Demographic Analysis at the University at Albany. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions as mentioned above.
Role of the funders/sponsors: None of the funders or sponsors of this research had any role in the design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Acknowledgments: The authors would like to thank Amanda Applegate for her comments on prior versions of this manuscript. The authors would also like to thank an anonymous reviewer for suggesting the inclusion of , among other important improvements. The ideas and opinions expressed herein are those of the authors alone, and endorsement by the authors' institutions or the funding agencies is not intended and should not be inferred.