New statistical methods under biased sampling and its application to medical studies

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In statistical analysis for medical studies, data sampling is often biased. In this research, new statistical methods have been developed for such situations. Firstly, we constructed a confidence interval which is robust to publication bias in meta-analysis. Then, for clinical trials of antihypertensive drugs, we proposed a method for evaluating causal interaction between the therapy and the treatment, controlling the effect of confounding factors. Finally, in survival analysis where the data is biased due to censoring, we considered a method which enables us to interpret a result of the analysis by the Cox regression model even when it is not correctly specified.