Ignorability and Bias in Clinical Trials
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Patient non-compliance and drop-out can bias analyses of clinical trial data. I describe a parametric model for treatment cross-over and drop-out and demonstrate how the concept of ignorability, originally defined for incomplete-data problems, can elucidate sources of bias in clinical trials. I discuss some implications of the theory and present simulation examples that illustrate the potential effects of non-ignorable cross-over and drop-out on bias and power.
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