Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

Published

Journal Article

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

Full Text

Duke Authors

Cited Authors

  • Suvak, MK; Walling, SM; Iverson, KM; Taft, CT; Resick, PA

Published Date

  • December 2009

Published In

Volume / Issue

  • 22 / 6

Start / End Page

  • 622 - 631

PubMed ID

  • 19937725

Pubmed Central ID

  • 19937725

Electronic International Standard Serial Number (EISSN)

  • 1573-6598

Digital Object Identifier (DOI)

  • 10.1002/jts.20476

Language

  • eng

Conference Location

  • United States