異質な部分集団によって構成されるデータに対し，予測力と解釈可能性を兼ね備えた統計的方法の構築に寄与することを目指した本研究の主な成果は，(1)予測力の改善指標となるIDIの改良版であるodds-IDIの開発，(2)臨床試験における諸種の状況を考慮した統計的解析法の提案，(3)異質性を考慮した生存時間回帰モデルの提案である．(1)では既存の指標を性能面で優越する結果が得られ，提案指標の理論的側面と解釈可能性を研究した．(2)では欠測などによって異質性が特徴づけられる場合の統計的解析法を研究した．(3)は潜在的な治癒群と未治癒群の混在を想定した場合の生存時間回帰モデルについて研究した．
Our research aims to contribute to the development of statistical methods with both predictive power and interpretability for data consisting of heterogeneous subpopulations. The main results are (1) the development of an improved version of the IDI, the odds-IDI, (2) the proposal of statistical analysis methods that take into account various situations in clinical trials, and (3) the proposal of a survival time regression model that takes heterogeneity into account. In (1), the proposed index outperforms existing indices in terms of performance, and the theoretical aspects and interpretability of the proposed index were studied. In (2), statistical analysis methods were studied for the cases where heterogeneity is characterized by missing data and so forth. In (3), a regression model for survival outcomes in the case of a mixture of potentially cured and uncured groups was studied.

研究種目 : 基盤研究 (C) (一般)
研究期間 : 2018～2023
課題番号 : 18K11197
研究分野 : 統計科学