Uncovering multiple pathways to substance use: a comparison of methods for identifying population subgroups

J Prim Prev. 2010 Dec;31(5-6):333-48. doi: 10.1007/s10935-010-0224-6.

Abstract

This paper describes and compares a selection of available modeling techniques for identifying homogeneous population subgroups in the interest of informing targeted substance use intervention. We present a nontechnical review of the common and unique features of three methods: (a) trajectory analysis, (b) functional hierarchical linear modeling (FHLM), and (c) decision tree methods. Differences among the techniques are described, including required data features, strengths and limitations in terms of the flexibility with which outcomes and predictors can be modeled, and the potential of each technique for helping to inform the selection of targets and timing of substance intervention programs.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Decision Trees
  • Female
  • Humans
  • Linear Models
  • Male
  • Models, Statistical*
  • Multivariate Analysis
  • Risk
  • Smoking / epidemiology*
  • Statistics, Nonparametric
  • Substance-Related Disorders / diagnosis
  • Substance-Related Disorders / epidemiology*
  • United States / epidemiology