Literature DB >> 30538054

Developmental considerations in survival models as applied to substance use research.

Kristina M Jackson1, Tim Janssen2.   

Abstract

Survival analysis is a class of models that are ideal for evaluating questions of timing of events, which makes them well-suited for modeling the development of a process such as initiation of substance use, development of addiction, or post-treatment recovery. The focus of this review paper is to demonstrate how survival models operate in a broader developmental framework and to offer guidance on selecting the appropriate model on the basis of the research question at hand. We provide a basic overview of survival models and then identify several key issues, explain how they pertain to research in the addiction field, and describe studies that utilize survival models to address questions about timing. We discuss the importance of carefully selecting the metric and origin of the time scale that corresponds to developmental process under investigation and we describe types of censoring/truncation. We describe the value of modeling covariates as time-invariant versus time-varying, and make the distinction between time-varying covariates and time-varying effects of covariates. We also explain how to test for substantive differences due to the timing of the assessment of the predictor. We finish the paper with a presentation of relatively novel extensions of survival models, including models that integrate standard statistical mediational analysis with discrete-time survival analysis, models that simultaneously consider order and timing of multiple events, and models that involve joint modeling of longitudinal and survival data. We also present our own substantive examples of various models in an Appendix containing annotated syntax and output.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Development; Event; Hazard; Initiation; Survival; Timing

Mesh:

Year:  2018        PMID: 30538054      PMCID: PMC6527490          DOI: 10.1016/j.addbeh.2018.11.028

Source DB:  PubMed          Journal:  Addict Behav        ISSN: 0306-4603            Impact factor:   3.913


  57 in total

1.  Choice of time-scale in Cox's model analysis of epidemiologic cohort data: a simulation study.

Authors:  Anne C M Thiébaut; Jacques Bénichou
Journal:  Stat Med       Date:  2004-12-30       Impact factor: 2.373

2.  Longitudinal patterns of binge drinking among first year college students with a history of tobacco use.

Authors:  Michael W Beets; Brian R Flay; Samuel Vuchinich; Kin-Kit Li; Alan Acock; Frank J Snyder
Journal:  Drug Alcohol Depend       Date:  2009-05-06       Impact factor: 4.492

3.  Twelve Frequently Asked Questions About Growth Curve Modeling.

Authors:  Patrick J Curran; Khawla Obeidat; Diane Losardo
Journal:  J Cogn Dev       Date:  2010

Review 4.  Basic concepts and methods for joint models of longitudinal and survival data.

Authors:  Joseph G Ibrahim; Haitao Chu; Liddy M Chen
Journal:  J Clin Oncol       Date:  2010-05-03       Impact factor: 44.544

5.  From alcohol initiation to tolerance to problems: Discordant twin modeling of a developmental process.

Authors:  Arielle R Deutsch; Wendy S Slutske; Michael T Lynskey; Kathleen K Bucholz; Pamela A F Madden; Andrew C Heath; Nicholas G Martin
Journal:  Dev Psychopathol       Date:  2016-07-15

6.  Sample-size formula for the proportional-hazards regression model.

Authors:  D A Schoenfeld
Journal:  Biometrics       Date:  1983-06       Impact factor: 2.571

7.  Marijuana use in the immediate 5-year premorbid period is associated with increased risk of onset of schizophrenia and related psychotic disorders.

Authors:  Mary E Kelley; Claire Ramsay Wan; Beth Broussard; Anthony Crisafio; Sarah Cristofaro; Stephanie Johnson; Thomas A Reed; Patrick Amar; Nadine J Kaslow; Elaine F Walker; Michael T Compton
Journal:  Schizophr Res       Date:  2016-01-17       Impact factor: 4.939

8.  Causal Mediation Analysis of Survival Outcome with Multiple Mediators.

Authors:  Yen-Tsung Huang; Hwai-I Yang
Journal:  Epidemiology       Date:  2017-05       Impact factor: 4.822

9.  Psychiatric and familial predictors of transition times between smoking stages: results from an offspring-of-twins study.

Authors:  Carolyn E Sartor; Hong Xian; Jeffrey F Scherrer; Michael T Lynskey; Alexis E Duncan; J Randolph Haber; Julia D Grant; Kathleen K Bucholz; Theodore Jacob
Journal:  Addict Behav       Date:  2007-09-08       Impact factor: 3.913

10.  Opioid withdrawal, craving, and use during and after outpatient buprenorphine stabilization and taper: a discrete survival and growth mixture model.

Authors:  Thomas F Northrup; Angela L Stotts; Charles Green; Jennifer S Potter; Elise N Marino; Robrina Walker; Roger D Weiss; Madhukar Trivedi
Journal:  Addict Behav       Date:  2014-09-28       Impact factor: 3.913

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  1 in total

1.  Parallel modeling of pain and depression in prediction of relapse during buprenorphine and naloxone treatment: A finite mixture model.

Authors:  Noel A Vest; Sterling McPherson; G Leonard Burns; Sarah Tragesser
Journal:  Drug Alcohol Depend       Date:  2020-02-26       Impact factor: 4.492

  1 in total

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