Modeling nonlinear time-dependent treatment effects: An application of the generalized time-varying effect model (TVEM)

Mariya P. Shiyko, Jack Burkhalter, Runze Li, Bernard J. Park

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Objective: The goal of this article is to introduce to social and behavioral scientists the generalized time-varying effect model (TVEM), a semiparametric approach for investigating time-varying effects of a treatment. The method is best suited for data collected intensively over time (e.g., experience sampling or ecological momentary assessments) and addresses questions pertaining to effects of treatment changing dynamically with time. Thus, of interest is the description of timing, magnitude, and (nonlinear) patterns of the effect. Method: Our presentation focuses on practical aspects of the model. A step-by-step demonstration is presented in the context of an empirical study designed to evaluate effects of surgical treatment on quality of life among early stage lung cancer patients during posthospitalization recovery (N = 59; 61% female, M age = 66.1 years). Frequency and level of distress associated with physical symptoms were assessed twice daily over a 2-week period, providing a total of 1,544 momentary assessments. Results: Traditional analyses (analysis of covariance [ANCOVA], repeated-measures ANCOVA, and multilevel modeling) yielded findings of no group differences. In contrast, generalized TVEM identified a pattern of the effect that varied in time and magnitude. Group differences manifested after Day 4. Conclusions: Generalized TVEM is a flexible statistical approach that offers insight into the complexity of treatment effects and allows modeling of nonnormal outcomes. The practical demonstration, shared syntax, and availability of a free set of macros aim to encourage researchers to apply TVEM to complex data and stimulate important scientific discoveries.

Original languageEnglish (US)
Pages (from-to)760-772
Number of pages13
JournalJournal of consulting and clinical psychology
Volume82
Issue number5
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Psychiatry and Mental health

Fingerprint Dive into the research topics of 'Modeling nonlinear time-dependent treatment effects: An application of the generalized time-varying effect model (TVEM)'. Together they form a unique fingerprint.

Cite this