Adaptive Hypothesis Testing
Adaptive Hypothesis Testing is a statistical inference framework within adaptive experimental designs that dynamically modifies hypotheses or testing procedures based on accumulating data while preserving Type I error control.
252
Publications
13.9K
Citations
445
Authors
287
Institutions
Publications per year
2017–2026
61
252
Adaptive Random Testing: The ART of test case diversity
Tsong Yueh Chen, Fei‐Ching Kuo, Robert Merkel et al. · Journal of Systems and Software · 2009 · 361 citations · Full text
Preserving Statistical Validity in Adaptive Data Analysis
Cynthia Dwork, Vitaly Feldman, Moritz Hardt et al. · 2015 · 265 citations
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287

University of Twente
Enschede, The Netherlands
9 h-index
11 publications
962 citations
Stanford University
Stanford, United States
8 h-index
15 publications
534 citations
Medical University of Vienna
Vienna, Austria
8 h-index
22 publications
969 citations
Statistics Austria
Vienna, Austria
6 h-index
15 publications
488 citations
Columbia University
New York, United States
6 h-index
9 publications
210 citations
University of Iowa
Iowa City, United States
5 h-index
7 publications
815 citations
University of Southern California
Los Angeles, United States
5 h-index
5 publications
229 citations
Swinburne University of Technology
Melbourne, Australia
4 h-index
11 publications
1.4K citations
1–8 of 287
16 publications · 627 citations
14
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12 publications · 878 citations
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12 publications · 525 citations
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Repository · 8 publications · 434 citations
8
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6 publications · 142 citations
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