Model-Driven Meta-Analyses for Informing Health Care
Academic Article
Overview
Research
Identity
Additional Document Info
View All
Overview
abstract
A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points.
author list (cited authors)
Brown, S. A., Becker, B. J., García, A. A., Brown, A., & Ramírez, G.
complete list of authors
Brown, Sharon A||Becker, Betsy Jane||García, Alexandra A||Brown, Adama||Ramírez, Gilbert