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Application of Correlated Time-to-Event Models to Ecological Momentary Assessment Data

Published online by Cambridge University Press:  01 January 2025

Emily A. Scherer Open the ORCID record for Emily A. Scherer [Opens in a new window] ,
Lin Huang  and
Lydia A. Shrier
Emily A. Scherer*
Affiliation:
Geisel School of Medicine at Dartmouth
Lin Huang
Affiliation:
Boston Children’s Hospital and Harvard Medical School
Lydia A. Shrier
Affiliation:
Boston Children’s Hospital and Harvard Medical School
*
Correspondence should be made to Emily A. Scherer, Division of Biostatistics, Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 03766 USA. Email: emily.a.scherer@dartmouth.edu
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Abstract

Ecological momentary assessment data consist of in-the-moment sampling several times per day aimed at capturing phenomena that are highly variable. When research questions are focused on the association between a construct measured repeatedly and an event that occurs sporadically over time interspersed between repeated measures, the data consist of correlated observed or censored times to an event. In such a case, specialized time-to-event models that account for correlated observations are required to properly assess the relationships under study. In the current study, we apply two time-to-event analysis techniques, proportional hazards, and accelerated failure time modeling, to data from a study of affective states and sexual behavior in depressed adolescents and illustrate differing interpretations from the models.

Keywords

ecological momentary assessmenttime to eventproportional hazards modelaccelerated failure time model
Type
Original Paper
Information
Psychometrika , Volume 82 , Issue 1 , March 2017 , pp. 233 - 244
Copyright
Copyright © 2016 The Psychometric Society

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