Empirical likelihood methods have emerged as a robust, non‐parametric framework for statistical inference that skilfully bypasses the need for strong parametric assumptions. By constructing likelihood ...
Evaluate arguments based on numerical evidence, construct appropriate graphics for a given data type to find patterns, and apply statistical inference methods of a given data structure and statistical ...
Introduces exploratory data analysis, probability theory, statistical inference, and data modeling. Topics include discrete and continuous probability distributions, expectation, laws of large numbers ...
In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...
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 ...
US FDA issues guidance on modernizing statistical methods for clinical trials: Maryland Wednesday, January 14, 2026, 09:00 Hrs [IST] The US Food and Drug Administration today publ ...
Statistical Science, Vol. 21, No. 4 (Nov., 2006), pp. 487-500 (14 pages) This review article provides an overview of recent work in the modeling and analysis of recurrent events arising in engineering ...
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