Latent Markov Model for Analyzing Temporal Configuration for Violence Profiles and Trajectories in a Sample of Batterers

Edward H. Ip, Alison Snow Jones, D. Alex Heckert, Qiang Zhang and Edward D. Gondolf
Additional contact information
Edward H. Ip: Wake Forest University School of Medicine, Winston-Salem, NC, USA, eip@wfubmc.edu
Alison Snow Jones: Drexel University, Philadelphia, PA, USA
D. Alex Heckert: Indiana University of Pennsylvania, Indiana, PA, USA
Qiang Zhang: Wake Forest University School of Medicine, Winston-Salem, NC, USA
Edward D. Gondolf: Indiana University of Pennsylvania, Indiana, PA, USA, Mid-Atlantic Addiction Research and Training Institute, Indiana, PA, USA

Sociological Methods & Research, 2010, vol. 39, issue 2, 222-255

Abstract: In this article, the authors demonstrate the utility of an extended latent Markov model for analyzing temporal configurations in the behaviors of a sample of 550 domestic violence batterers. Domestic violence research indicates that victims experience a constellation of abusive behaviors rather than a single type of violent outcome. There is also evidence that observed behaviors are highly dynamic, with batterers cycling back and forth between periods of no abuse and violent or controlling behavior. These issues pose methodological challenges for social scientists. The extended latent Markov method uses multiple indicators to characterize batterer behaviors and relates the trajectories of violent states to predictors of abuse at baseline. The authors discuss both methodological refinements of the latent Markov models and policy implications of the data analysis.

Keywords: domestic violence; hidden Markov model; latent trait regression; trajectory analysis; abusive behavior; latent variable; junction tree (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:39:y:2010:i:2:p:222-255

DOI: 10.1177/0049124110378095

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