Missing Data Adjustment
Missing Data Adjustment is a statistical method designed to correct for biases introduced by incomplete data within propensity score analyses by incorporating techniques such as multiple imputation or inverse probability weighting to ensure valid causal inferences.
391
Publications
31.6K
Citations
1.1K
Authors
533
Institutions
Publications per year
2017–2026
105
391
Janus Christian Jakobsen, Christian Gluud, Jørn Wetterslev et al. · BMC Medical Research Methodology · 2017 · 2.8K citations · Full text
Statistical Adjustment of Data
R. L. Anderson, W. Edwards Deming · Southern Economic Journal · 1944 · 776 citations
1–5 of 391
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London School of Hygiene & Tropical Medicine, United Kingdom
7 publications · 2K citations
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533
Harvard University
Cambridge, United States
16 h-index
51 publications
3.7K citations
London School of Hygiene & Tropical Medicine
London, United Kingdom
14 h-index
23 publications
4.5K citations
MRC Biostatistics Unit
Cambridge, United Kingdom
14 h-index
26 publications
5.7K citations
University of Michigan
Ann Arbor, United States
13 h-index
18 publications
1.2K citations
University College London
London, United Kingdom
11 h-index
14 publications
1.5K citations

Johns Hopkins University
Baltimore, United States
11 h-index
25 publications
1.4K citations
University of Washington
Seattle, United States
11 h-index
18 publications
916 citations
University of California, Los Angeles
Los Angeles, United States
10 h-index
22 publications
2.9K citations
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42 publications · 3.9K citations
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18 publications · 3.5K citations
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15 publications · 1.2K citations
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AJE · 12 publications · 1.2K citations
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14 publications · 591 citations
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