Analysis of randomized comparative clinical trial data for personalized treatment selections
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Publication:3303673
DOI10.1093/biostatistics/kxq060zbMath1437.62406OpenAlexW2153646525WikidataQ33704826 ScholiaQ33704826MaRDI QIDQ3303673
L. Tian, L. J. Wei, Peggy H. Wong, Tianxi Cai
Publication date: 4 August 2020
Published in: Biostatistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biostatistics/kxq060
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Cites Work
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- Local Likelihood Estimation
- Evaluating Markers for Selecting a Patient's Treatment
- Improving Efficiency of Inferences in Randomized Clinical Trials Using Auxiliary Covariates
- Transformations in Density Estimation
- Bandwith selection for the smoothing of distribution functions
- Simple Transformation Techniques for Improved Non‐parametric Regression
- Model evaluation based on the sampling distribution of estimated absolute prediction error
- Patterns of treatment effects in subsets of patients in clinical trials