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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
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Combining propensity score matching and group-based trajectory analysis in an observational study.

Amelia Haviland1, Daniel S Nagin, Paul R Rosenbaum

  • 1Statistics Group, RAND Corporation, Pittsburgh, PA, USA.

Psychological Methods
|September 6, 2007
PubMed
Summary

This study used propensity scores and trajectory groups to analyze the impact of gang joining on subsequent violence in boys. Variable ratio matching improved efficiency and reduced bias in observational studies.

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Area of Science:

  • Social Sciences
  • Criminology
  • Epidemiology

Background:

  • Observational studies require advanced methods to control for confounding variables.
  • Trajectory groups can characterize subjects with no good matches and define groups for varied treatment effect analysis.
  • Previous research highlights the need for robust statistical techniques in nonrandomized studies.

Purpose of the Study:

  • To assess the impact of gang joining at age 14 on subsequent violence.
  • To control for baseline measures of outcome and observed covariates in a Montreal-based cohort.
  • To illustrate the application of propensity scores and trajectory groups in observational research.

Main Methods:

  • Propensity scores and trajectory groups were used to balance covariates and control for pretreatment outcomes.
  • Boys were divided into trajectory groups based on violence levels from ages 11 to 13.
  • Optimal variable ratio matching using propensity scores, Mahalanobis distances, and combinatorial optimization was employed.

Main Results:

  • Variable ratio matching demonstrated greater efficiency compared to pair matching.
  • This method also achieved greater bias reduction than fixed-ratio matching.
  • Sensitivity analysis examined the potential impact of unmeasured confounders.

Conclusions:

  • Propensity scores and trajectory groups are effective tools for analyzing observational data.
  • Variable ratio matching offers advantages in efficiency and bias reduction for such studies.
  • Careful consideration of potential unmeasured confounders is crucial in violence research.