4 papers
Design and Analysis Considerations for Causal Inference under Two-Phase Sampling in Observational Studies
Kazuharu Harada, Masataka Taguri
Two-phase sampling is a simple and cost-effective estimation strategy in survey sampling and is widely used in practice. Because the phase-2 sampling probability typically depends…
On the uncertainty from the first-stage estimation of prognostic covariate adjustment in randomized controlled trials
Nodoka Seya, Masataka Taguri
Prognostic covariate adjustment (PROCOVA) is a two-sample two-stage estimation method for covariate adjustment in randomized controlled trials. In the first stage, a prognostic sco…
Simultaneous Modeling of Disease Screening and Severity Prediction: A Multi-task and Sparse Regularization Approach
Kazuharu Harada, Shuichi Kawano, Masataka Taguri
Identifying clinically relevant biomarkers and developing predictive models are central challenges in biomedical research. Biomarkers are commonly used for disease screening, and s…
False Discovery Rate Control for Confounder Selection Using Mirror Statistics
Kazuharu Harada, Masataka Taguri
While data-driven confounder selection requires careful consideration, it is frequently employed in observational studies. Widely recognized criteria for confounder selection inclu…