Longitudinal Propensity Score Matching: A Demonstration of Counterfactual Conditions Adjusted for Longitudinal Clustering
Given the challenges of conducting experimental studies in criminology and criminal justice, propensity score matching (PSM) represents one of the most commonly used techniques for evaluating the efficacy of treatment conditions on future behavior. Nevertheless, current iterations of PSM fail to adj...
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| Contributors: | ; ; |
| Format: | Electronic Article |
| Language: | English |
| Published: |
[2021]
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| In: |
Journal of quantitative criminology
Year: 2021, Volume: 37, Issue: 1, Pages: 267-301 |
| Online Access: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | |
| Check availability: | HBZ Gateway |
| Keywords: |
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| 520 | |a Given the challenges of conducting experimental studies in criminology and criminal justice, propensity score matching (PSM) represents one of the most commonly used techniques for evaluating the efficacy of treatment conditions on future behavior. Nevertheless, current iterations of PSM fail to adjust for the effects of longitudinal clustering on participant exposure to treatment conditions. The current study presents and evaluates longitudinal PSM (LPSM) as an alternative method for assessing the effects of a treatment condition on future behavior. LPSM adjusts for the effects of longitudinal clustering (i.e., clustered error) by assuming that the association between a cross-sectional predictor and a treatment condition varies depending upon the time at which the treatment was administered. | ||
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| 650 | 4 | |a Longitudinal data | |
| 650 | 4 | |a Longitudinal clustering | |
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