Examining How Context Changes Intervention Impact: The Use of Effect Sizes in Multilevel Mixture Meta-Analysis
- PMID: 20585469
- PMCID: PMC2888146
- DOI: 10.1111/j.1750-8606.2008.00065.x
Examining How Context Changes Intervention Impact: The Use of Effect Sizes in Multilevel Mixture Meta-Analysis
Abstract
In describing the impact of an intervention, a single effect size, odds ratio, or other summary measure is often employed. This single measure is useful in calibrating the effect of one intervention against others, but it is less meaningful when the intervention displays variation in impact. A single intervention trial can show differential effects when subgroups respond differentially, when impact varies by environmental context, or when there is varying impact with different outcome measures or across follow-up time. This article presents a multilevel mixture modeling approach for meta-analyses that summarizes these sources of impact variation across trials and measured outcomes.
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References
-
- Asparouhov T, Muthén BO. Multilevel mixture models. In: Hancock GR, Samuelsen KM, editors. Advances in latent variable mixture models. Charlotte, NC: Information Age Publishing; 2008. pp. 27–51.
-
- Berlin JA, Santanna J, Schmid CH, Szczech LA, Feldman HI. Individual patient-versus group-level data meta-regressions for the investigation of treatment effect modifiers: Ecological bias rears its ugly head. Statistics in Medicine. 2002;21:371–387. - PubMed
-
- Brown CH, Berndt D, Brinales JM, Zong X, Bhagwat D. Evaluating the evidence of effectiveness for preventive interventions: Using a registry system to influence policy through science. Addictive Behaviors. 2000;25:955–964. - PubMed
-
- Brown CH, Faraone SV. Prevention of schizophrenia and psychotic behavior: Definitions and methodologic issues. In: Stone WS, Faraone SV, Tsuang MT, editors. Early clinical intervention and prevention in schizophrenia. Totowa, NJ: Humana Press; 2004. pp. 255–284.
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