Mark E. Glickman

123 papers receiving 4.7k citations

Hit Papers

False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies 2014 · 1.1k citations
1.1k19982026200720162505007501000

Peers

Mark E. Glickman
Comparison fields: 5 of 197
  • Family Practice 180
  • Geriatrics and Gerontology 223
  • Cardiology and Cardiovascular Medicine 1.0k
  • Statistics and Probability 276
  • Economics and Econometrics 924
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Citations per year

Countries citing papers authored by Mark E. Glickman

Since Specialization
Citations

This map shows the geographic impact of Mark E. Glickman'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 Mark E. Glickman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark E. Glickman more than expected).

Fields of papers citing papers by Mark E. Glickman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark E. Glickman. 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 Mark E. Glickman. The network helps show where Mark E. Glickman may publish in the future.

Co-authors

The 25 scholars most cited alongside Mark E. Glickman, 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 Mark E. Glickman Line = papers co-authored together Mark E. Glickman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.

#Work
1
False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
Hit paper breakdown →
20141091
2
Inadequate Management of Blood Pressure in a Hypertensive Population
Hit paper breakdown →
1998764
3 1997361
4 1999227
5 2011174
6 2012138
7 2003120
8 2007106
9 200587
10 199882
11 201080
12 200170
13 201065
14 200659
15 201056
16 201254
17 202154
18 201852
19 200648
20 200748

About Mark E. Glickman

Mark E. Glickman is a scholar working on Statistics and Probability, Family Practice, Economics and Econometrics, General Health Professions and Social Psychology, having authored 127 papers that have together received 5.0k indexed citations. Recurring topics across this work include Sports Analytics and Performance (19 papers), Blood Pressure and Hypertension Studies (9 papers), Healthcare Policy and Management (8 papers), Mental Health Treatment and Access (8 papers), Health Systems, Economic Evaluations, Quality of Life (7 papers), Family Support in Illness (7 papers), Primary Care and Health Outcomes (7 papers) and Advanced Causal Inference Techniques (7 papers). The work is most often cited by research in Family Practice (180 citations), Geriatrics and Gerontology (223 citations), Cardiology and Cardiovascular Medicine (1.0k citations), Statistics and Probability (276 citations) and Economics and Econometrics (924 citations). Mark E. Glickman has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Mark Schultz, Sowmya R. Rao, Dan R. Berlowitz, Robert H. Friedman, Arlene S. Ash, Boris Kader, Sharon‐Lise T. Normand, Constantine Gatsonis, Elaine C. Hickey and Mark A. Moskowitz. Their work appears in journals such as Journal of Quantitative Analysis in Sports, Medical Care, Journal of the American Statistical Association, JAMA Network Open and The Journal of Behavioral Health Services & Research.

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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