Methods For Minimizing Bias From Missing Data In Critical Care Research
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Missing data is a common, yet often overlooked, source of bias that plagues both observational and randomized studies. Failure to appropriately account for missing data can create selection bias that may lead to spurious, unreplicable findings. This webcast from Discovery, the Critical Care Research Network, will describe the biases that can be created by missing data and provide an overview of effective methodology for reducing missing data bias.