Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
Papers in this series provide tutorials on statistical methods that are used in precision oncology, such as methods in discovery phase, diagnostics, and drug development. The goal of the series is to ...
Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
Test equating constitutes a critical element of modern assessment practices, ensuring that scores from different test forms are directly comparable. Recent advancements have pooled statistical ...
Precision oncology exploits genomic, immunologic, and other biomarkers to drive discovery, drug development, and clinical care for patients with cancer. Precision oncology helps devise individualized ...
An ad hoc panel of nationally renowned experts in social science research, computing technology, statistical methods, privacy, and use of alternative data sources in the United States and abroad will ...
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