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

Author

Listed:
  • Emily A. Scherer

    (Geisel School of Medicine at Dartmouth)

  • Lin Huang

    (Boston Children’s Hospital and Harvard Medical School)

  • Lydia A. Shrier

    (Boston Children’s Hospital and Harvard Medical School)

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.

Suggested Citation

  • Emily A. Scherer & Lin Huang & Lydia A. Shrier, 2017. "Application of Correlated Time-to-Event Models to Ecological Momentary Assessment Data," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 233-244, March.
    • Handle: RePEc:spr:psycho:v:82:y:2017:i:1:d:10.1007_s11336-016-9495-z
    DOI: 10.1007/s11336-016-9495-z
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    References listed on IDEAS

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    1. Stephen L. Rathbun & Xiao Song & Benjamin Neustifter & Saul Shiffman, 2013. "Survival analysis with time varying covariates measured at random times by design," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(3), pages 419-434, May.
    2. Donald Hedeker & Robin J. Mermelstein & Hakan Demirtas, 2008. "An Application of a Mixed-Effects Location Scale Model for Analysis of Ecological Momentary Assessment (EMA) Data," Biometrics, The International Biometric Society, vol. 64(2), pages 627-634, June.
    3. Zhezhen Jin & D. Y. Lin & Zhiliang Ying, 2006. "On least-squares regression with censored data," Biometrika, Biometrika Trust, vol. 93(1), pages 147-161, March.
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