Study on statistical transformation model in medical data

2017 Fiscal Year Final Research Report

• Project/Area Number: 16H07465
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Single-year Grants
• Research Field: Statistical science
• Research Institution: University of Tsukuba (2017); National Center of Neurology and Psychiatry (2016)
• Principal Investigator: Maruo Kazushi 筑波大学, 医学医療系, 准教授 (10777999)
• Research Collaborator: GOSHO Masahiko 筑波大学, 医学医療系, 准教授 ; NOMA Hisashi 統計数理研究所, データ科学研究系, 准教授
• Project Period (FY): 2016-08-26 – 2018-03-31
• Keywords: 治療効果の解釈可能性

Outline of Final Research Achievements

We derived results for inference on parameters of the multivariate regression model with the Box-Cox transformation where transformation parameters differ for each visit and group based on the asymptotic theory approach. We also provided a robust variance estimator of the maximum likelihood estimator of the parameters of this model in consideration of the model misspecifications.
Using these results, we developed an inference procedure for the difference of the model median between treatment groups at the specified occasion in the context of mixed effects models for repeated measures analysis for randomized clinical trials, which provided interpretable estimates of the treatment effect. From simulation studies, it was shown that our proposed method had moderate or high performance for bias compared with the existing methods.

Free Research Field

生物統計学