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Methods for trend estimation from summarized dose-response data, with applications to meta-analysis.

American Journal of Epidemiology

Alcohol Drinking, Risk Factors, Odds Ratio, Meta-Analysis as Topic, Logistic Models, Least-Squares Analysis, Humans, Dose-Response Relationship, Drug, etiology, epidemiology, Breast Neoplasms, trends, adverse effects

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      Meta-analysis often requires pooling of correlated estimates to compute regression slopes (trends) across different exposure or treatment levels. The authors propose two methods that account for the correlations but require only the summary estimates and marginal data from the studies. These methods provide more efficient estimates of regression slope, more accurate variance estimates, and more valid heterogeneity tests than those previously available. One method also allows estimation of nonlinear trend components, such as quadratic effects. The authors illustrate these methods in a meta-analysis of alcohol use and breast cancer.

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