Suhail A R Doi1, Jan J Barendregt2, Chalapati Rao2. 1. School of Population Health, University of Queensland, Brisbane, Australia. Electronic address: sardoi@gmx.net. 2. School of Population Health, University of Queensland, Brisbane, Australia.
Abstract
OBJECTIVE: To demonstrate why meta-analytic methods need modification before they can be used to aggregate rates or effect sizes in outcomes research, under the constraint of no common underlying effect or rate. METHODS: Studies are presented that require different types of risk adjustment. First, we demonstrate using rates that external risk adjustment through standardization can be achieved using modified meta-analytic methods, but only with a model that allows input of user-defined weights. Next, we extend these observations to internal risk adjustment of comparative effect sizes. RESULTS: We show that this procedure produces identical results to conventional age standardization if a rate is being standardized for age. We also demonstrate that risk adjustment of effect sizes can be achieved with this modified method but cannot be done using standard meta-analysis. CONCLUSIONS: We conclude that this method allows risk adjustment to be performed in situations in which currently the fixed- or random-effects methods of meta-analysis are inappropriately used. The latter should be avoided when the underlying aim is risk adjustment rather than meta-analysis.
OBJECTIVE: To demonstrate why meta-analytic methods need modification before they can be used to aggregate rates or effect sizes in outcomes research, under the constraint of no common underlying effect or rate. METHODS: Studies are presented that require different types of risk adjustment. First, we demonstrate using rates that external risk adjustment through standardization can be achieved using modified meta-analytic methods, but only with a model that allows input of user-defined weights. Next, we extend these observations to internal risk adjustment of comparative effect sizes. RESULTS: We show that this procedure produces identical results to conventional age standardization if a rate is being standardized for age. We also demonstrate that risk adjustment of effect sizes can be achieved with this modified method but cannot be done using standard meta-analysis. CONCLUSIONS: We conclude that this method allows risk adjustment to be performed in situations in which currently the fixed- or random-effects methods of meta-analysis are inappropriately used. The latter should be avoided when the underlying aim is risk adjustment rather than meta-analysis.
Keywords:
age standardization; burden of disease; fixed-effects model; meta-analysis; population standardization; quality-effects model; random-effects model