Daniel Feldman

1.4k citations
22 papers · 521 · h-index 9

Impact in

    • Advanced Causal Inference Techniques
    • Statistical Methods in Clinical Trials
    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference

Papers in

Daniel Feldman

20 papers receiving 488 citations

Peers

Daniel Feldman
Comparison fields: 5 of 98
  • Statistics and Probability 175
  • Family Practice 23
  • Organizational Behavior and Human Resource Management 65
  • Public Administration 14
  • General Health Professions 65
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Adeniyi J. Adewale United States
Athanassios Vozikis Greece
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Feldman

Since Specialization
Citations

This map shows the geographic impact of Daniel Feldman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Feldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Feldman more than expected).

Fields of papers citing papers by Daniel Feldman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Feldman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Feldman. The network helps show where Daniel Feldman may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Feldman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Feldman Line = papers co-authored together Daniel Feldman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991219
2 1990123
3 200952
4 199140
5 200918
6 201715
7 20169
8 19919
9 19668
10 20156
11 20225
12 20095
13 20092
14 20092
15 20092
16 20221
17 20221
18 20221
19 20051
20
Compliance as an Explanatory Variable in Clinical Trials with Comments and Rejoinder
19911

About Daniel Feldman

Daniel Feldman is a scholar working on Surgery, Cardiology and Cardiovascular Medicine, Economics and Econometrics, Biomedical Engineering and Public Health, Environmental and Occupational Health, having authored 22 papers that have together received 521 indexed citations. Recurring topics across this work include Coronary Interventions and Diagnostics (3 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Antiplatelet Therapy and Cardiovascular Diseases (3 papers), Advanced Causal Inference Techniques (2 papers), Cardiac and Coronary Surgery Techniques (2 papers), Statistical Methods in Clinical Trials (2 papers), Breast Implant and Reconstruction (2 papers) and Venous Thromboembolism Diagnosis and Management (1 paper). The work is most often cited by research in Statistics and Probability (175 citations), Family Practice (23 citations), Organizational Behavior and Human Resource Management (65 citations), Public Administration (14 citations) and General Health Professions (65 citations). Daniel Feldman has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include B. Efron, Brad Efron, Kevin Small, Oren M. Tepper, Jacob G. Unger, Naveen Kumar, Mihye Choi, Nolan S. Karp, Colleen M. Brophy and Joyce Cheung‐Flynn. Their work appears in journals such as Reviews in Cardiovascular Medicine, Journal of the American Statistical Association, Circulation, The American Journal of Gastroenterology and Journal of Clinical Oncology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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