- Statist. Surv.
- Volume 13 (2019), 150-180.
Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists
Researchers are sometimes interested in predicting a distal or external outcome (such as smoking cessation at follow-up) from the trajectory of an intensively recorded longitudinal variable (such as urge to smoke). This can be done in a semiparametric way via scalar-on-function regression. However, the resulting fitted coefficient regression function requires special care for correct interpretation, as it represents the joint relationship of time points to the outcome, rather than a marginal or cross-sectional relationship. We provide practical guidelines, based on experience with scientific applications, for helping practitioners interpret their results and illustrate these ideas using data from a smoking cessation study.
Statist. Surv., Volume 13 (2019), 150-180.
Received: November 2018
First available in Project Euclid: 6 November 2019
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Dziak, John J.; Coffman, Donna L.; Reimherr, Matthew; Petrovich, Justin; Li, Runze; Shiffman, Saul; Shiyko, Mariya P. Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists. Statist. Surv. 13 (2019), 150--180. doi:10.1214/19-SS126. https://projecteuclid.org/euclid.ssu/1573009381