IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v82y2017i1d10.1007_s11336-016-9495-z.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11336-016-9495-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11336-016-9495-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Linzhi & Zhang, Jiajia, 2010. "An EM-like algorithm for the semiparametric accelerated failure time gamma frailty model," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1467-1474, June.
    2. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
    3. Choi, Taehwa & Kim, Arlene K.H. & Choi, Sangbum, 2021. "Semiparametric least-squares regression with doubly-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
    4. Fan, Caiyun & Lu, Wenbin & Zhou, Yong, 2021. "Testing error heterogeneity in censored linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    5. Min Zhang & Marie Davidian, 2008. "“Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data," Biometrics, The International Biometric Society, vol. 64(2), pages 567-576, June.
    6. Hedeker, Donald & Nordgren, Rachel, 2013. "MIXREGLS: A Program for Mixed-Effects Location Scale Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i12).
    7. Patrick Sturgis & Ian Brunton-Smith & Jonathan Jackson, 2021. "Trust in science, social consensus and vaccine confidence," Nature Human Behaviour, Nature, vol. 5(11), pages 1528-1534, November.
    8. Olbrich, Lukas & Kosyakova, Yuliya & Sakshaug, Joseph W., 2022. "The reliability of adult self-reported height: The role of interviewers," Economics & Human Biology, Elsevier, vol. 45(C).
    9. Leonardo Grilli & Carla Rampichini, 2015. "Specification of random effects in multilevel models: a review," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 967-976, May.
    10. Manuel Oviedo-de La Fuente & Celestino Ordóñez & Javier Roca-Pardiñas, 2020. "Functional Location-Scale Model to Forecast Bivariate Pollution Episodes," Mathematics, MDPI, vol. 8(6), pages 1-12, June.
    11. Yu, Lili & Zhao, Yichuan, 2024. "Laplace approximated quasi-likelihood method for heteroscedastic survival data," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    12. Lili Yu & Liang Liu & Ding-Geng Chen, 2019. "A homoscedasticity test for the accelerated failure time model," Computational Statistics, Springer, vol. 34(1), pages 433-446, March.
    13. Zou, Yubo & Zhang, Jiajia & Qin, Guoyou, 2011. "A semiparametric accelerated failure time partial linear model and its application to breast cancer," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1479-1487, March.
    14. Bao, Yanchun & He, Shuyuan & Mei, Changlin, 2007. "The Koul-Susarla-Van Ryzin and weighted least squares estimates for censored linear regression model: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6488-6497, August.
    15. Jung-Yu Cheng & Shinn-Jia Tzeng, 2014. "Quantile regression of right-censored length-biased data using the Buckley–James-type method," Computational Statistics, Springer, vol. 29(6), pages 1571-1592, December.
    16. Ersin Yılmaz & Syed Ejaz Ahmed & Dursun Aydın, 2020. "A-Spline Regression for Fitting a Nonparametric Regression Function with Censored Data," Stats, MDPI, vol. 3(2), pages 1-17, May.
    17. Maria Iannario & Maria Kateri & Claudia Tarantola, 2024. "Modelling scale effects in rating data: a Bayesian approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4053-4071, October.
    18. Shelley A. Blozis, 2022. "A Latent Variable Mixed-Effects Location Scale Model with an Application to Daily Diary Data," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1548-1570, December.
    19. Wenjing Yin & Sihai Dave Zhao & Feng Liang, 2022. "Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(2), pages 282-318, April.
    20. Xie, Shangyu & Wan, Alan T.K. & Zhou, Yong, 2015. "Quantile regression methods with varying-coefficient models for censored data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 154-172.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:82:y:2017:i:1:d:10.1007_s11336-016-9495-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.