Dose-response relationship model has been widely used in epidemiology studies, as well as in evidence-based medicine area. In dose-response meta-analysis, the results are highly depended on the raw data. However, many primary studies did not provide sufficient data and led the difficulties in data analysis. The efficiency and response rate of collecting the raw data from original authors were always low, thus, evaluating and transforming the missing data is very important. In this paper, we summarized several types of missing data, and introduced how to estimate the missing data and transform the effect measure using the existed information.
Citation: XUChang, LIUTong-zu, KUANGXin-ying, ZHANGYong-gang, WENGHong, ZHANGChao. How to Estimate the Missing Data and Transform the Effect Measure in Dose-response Meta-analysis. Chinese Journal of Evidence-Based Medicine, 2015, 15(8): 984-987. doi: 10.7507/1672-2531.20150164 Copy
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