Model-Driven Meta-Analyses for Informing Health Care Academic Article uri icon

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of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses.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

publication date

  • January 2014