Bias Control
Bias Control is a set of methodological strategies in experimental design that systematically prevent, detect, and adjust for nonrandom sources of error in the selection, allocation, measurement, or treatment of study units, thereby minimizing systematic bias and protecting the validity of causal inferences.
3.5K
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536K
Citations
7.6K
Authors
2.2K
Institutions
Publications per year
2017–2026
1.1K
3.5K
The Cochrane Collaboration's tool for assessing risk of bias in randomised trials
Julian P. T. Higgins, Doug Altman, Peter C Gøtzsche et al. · BMJ · 2011 · 34.2K citations · Full text
Sample Selection Bias as a Specification Error
James J. Heckman · Econometrica · 1979 · 28.9K citations
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University of California, Los Angeles, United States
18 publications · 4.1K citations
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Harvard University
Cambridge, United States
59 h-index
226 publications
45.7K citations
University of Pennsylvania
Philadelphia, United States
43 h-index
155 publications
34.1K citations
University of California, Berkeley
Berkeley, United States
37 h-index
83 publications
11K citations
Stanford University
Stanford, United States
37 h-index
110 publications
25.9K citations

University of Bristol
Bristol, United Kingdom
37 h-index
157 publications
131.4K citations
University of California, Los Angeles
Los Angeles, United States
36 h-index
75 publications
10.7K citations
University of Michigan
Ann Arbor, United States
36 h-index
99 publications
13.2K citations
Yale University
New Haven, United States
33 h-index
74 publications
7.1K citations
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111 publications · 13.4K citations
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64 publications · 12.4K citations
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AJE · 53 publications · 12.5K citations
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57 publications · 7.2K citations
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Repository · 79 publications · 7.8K citations
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