David G. Kleinbaum

126 papers receiving 23.8k citations

Hit Papers

Survival Analysis 2011 · 619 citations
61919782026199420102.0k4.0k6.0k

Peers

David G. Kleinbaum
Comparison fields: 5 of 239
  • Medical Laboratory Technology 471
  • Health 1.5k
  • Statistics and Probability 1.1k
  • General Health Professions 2.8k
  • Public Health, Environmental and Occupational Health 2.6k
Replace J. Richard Landis with:
J. Richard Landis United States
David W. Hosmer United States
Stephen D. Walter Canada
Lawrence L. Kupper United States
Stanley Lemeshow United States
P.J. Devereaux Canada
Nan M. Laird United States
Gary G. Koch United States
Lesley Stewart United Kingdom
Cynthia D. Mulrow United States
David G. Kleinbaum relative to J. Richard Landis United States J. Richard Landis's profile →
Citations per field
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J. Richard Landis · 1×
Citations per year

Countries citing papers authored by David G. Kleinbaum

Since Specialization
Citations

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

Fields of papers citing papers by David G. Kleinbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David G. Kleinbaum. 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 David G. Kleinbaum. The network helps show where David G. Kleinbaum may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 201930
2 201714
3 20164
4 201621
5 201520
6 201516
7 20154
8 20149
9 201216
10 201056
11 200818
12 200871
13 200635
14 2005174
15 200590
16 2005151
17 199839
18 199429
19 198999
20 197376

About David G. Kleinbaum

David G. Kleinbaum is a scholar working on Applied Microbiology and Biotechnology, Statistics and Probability, Medical Laboratory Technology, General Health Professions and Health, having authored 128 papers that have together received 25.4k indexed citations. Recurring topics across this work include Child Nutrition and Water Access (8 papers), Obesity, Physical Activity, Diet (7 papers), Global Maternal and Child Health (7 papers), Statistical Methods and Bayesian Inference (7 papers), Breastfeeding Practices and Influences (6 papers), Statistical Methods and Inference (6 papers), Adolescent Sexual and Reproductive Health (5 papers) and Primary Care and Health Outcomes (5 papers). The work is most often cited by research in Medical Laboratory Technology (471 citations), Health (1.5k citations), Statistics and Probability (1.1k citations), General Health Professions (2.8k citations) and Public Health, Environmental and Occupational Health (2.6k citations). David G. Kleinbaum has collaborated with scholars based in United States, Australia and Bangladesh. Frequent co-authors include Lawrence L. Kupper, Keith E. Muller, Esteban Walker, Hal Morgenstern, Mitchel Klein, Steve Selvin, Lawrence S. Mayer, Helen T. Bhattacharyya, S J Pocock and L L Kupper. Their work appears in journals such as American Journal of Public Health, Journal of the American Statistical Association, International Journal of Epidemiology, The American Statistician and Infection Control and Hospital Epidemiology.

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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