1 citations · 1 across the 4 of their papers we have counts for
6 papers
Distributional Flexibility under Box-Cox Normality: A Theoretical and Empirical Evaluation of the Power-Normal Distribution
Kazushi Maruo, Yusuke Yamaguchi, Ryota Ishii +2
Methods based on Box-Cox models have recently been developed for inference on clinically interpretable treatment effects in clinical trials. These methods model marginal outcome di…
Validity of MMRM-based hypothesis testing under missing-not-at-random mechanisms
Kazushi Maruo, Ryota Ishii, Yusuke Yamaguchi +3
In randomized clinical trials with longitudinal continuous outcomes, missing-not-at-random (MNAR) missingness often motivates conservative alternatives to mixed models for repeated…
A flexible framework for treatment effect inference in longitudinal clinical studies with skewed outcomes
Kazushi Maruo, Ryota Ishii, Yusuke Yamaguchi +3
Longitudinal continuous outcomes in clinical trials are commonly analyzed using mixed models for repeated measures (MMRM) under normality assumptions. However, many clinical outcom…
Modification and extension of the Bayesian clinical trial design using external data for single-arm and hybrid-controlled trials
Wataru Murasaki, Tomohiro Ohigashi, Ryota Ishii +2
Limited patient availability complicates sample size determination in pediatric clinical trials. Although Bayesian methods incorporating external data offer a solution, rigorously…
Posterior Quantification of Borrowing from Multiple Historical Control Data in Bayesian Dynamic Borrowing Methods: A Scoping Review
Tomohiro Ohigashi, Wataru Murasaki, Masahiko Gosho
Bayesian dynamic borrowing methods incorporate historical control data into current clinical trial analyses while allowing the degree of borrowing to depend on the compatibility be…
Nonparametric Bayesian approach for dynamic borrowing of historical control data
Tomohiro Ohigashi, Kazushi Maruo, Takashi Sozu +1
When incorporating historical control data into the analysis of current randomized controlled trial data, it is critical to account for differences between the datasets. When the c…