A time-varying effect model for studying gender differences in health behavior

Songshan Yang, James A. Cranford, Runze Li, Robert A. Zucker, Anne Buu

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This study proposes a time-varying effect model that can be used to characterize gender-specific trajectories of health behaviors and conduct hypothesis testing for gender differences. The motivating examples demonstrate that the proposed model is applicable to not only multi-wave longitudinal studies but also short-term studies that involve intensive data collection. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size and the number of time points increase. In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all combinations of sample size and number of time points. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size and the number of time points are larger.

Original languageEnglish (US)
Pages (from-to)2812-2820
Number of pages9
JournalStatistical Methods in Medical Research
Volume26
Issue number6
DOIs
StatePublished - Dec 1 2017

Fingerprint

Gender Differences
Health Behavior
Time-varying
Sample Size
Health
Hypothesis Testing
Trajectory
Type I Error Rate
Significance level
Longitudinal Study
Null hypothesis
Simulation Study
Model
Longitudinal Studies
Alternatives
Demonstrate

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

Cite this

Yang, Songshan ; Cranford, James A. ; Li, Runze ; Zucker, Robert A. ; Buu, Anne. / A time-varying effect model for studying gender differences in health behavior. In: Statistical Methods in Medical Research. 2017 ; Vol. 26, No. 6. pp. 2812-2820.
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A time-varying effect model for studying gender differences in health behavior. / Yang, Songshan; Cranford, James A.; Li, Runze; Zucker, Robert A.; Buu, Anne.

In: Statistical Methods in Medical Research, Vol. 26, No. 6, 01.12.2017, p. 2812-2820.

Research output: Contribution to journalArticle

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