Abstract:We introduce causal inference reasoning to crossover trials, with a focus on thorough QT (TQT) studies. For such trials, we propose different sets of assumptions and consider their impact on the modeling strategy and estimation procedure. We show that unbiased estimates of a causal treatment effect are obtained by a g‐computation approach in combination with weighted least squares predictions from a working regression model. Only a few natural requirements on the working regression and weighting matrix are nee… Show more
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