N. E. Breslow

49.7k citations
111 papers · 40.1k indexed · 13 hit papers · h-index 56

N. E. Breslow

109 papers receiving 37.5k citations

Hit Papers

Approximate Inference in Generalized Linear Mixed Models1.3k19742026199120082.0k4.0k6.0k

Peers

N. E. Breslow
Comparison fields: 5 of 223
  • Statistics and Probability 8.0k
  • Oncology 6.1k
  • Pathology and Forensic Medicine 3.6k
  • Pulmonary and Respiratory Medicine 5.8k
  • Cancer Research 2.4k
Replace Nan M. Laird with:
Nan M. Laird United States
Nathan Mantel United States
Richard Simon United States
Ross L. Prentice United States
Frank E. Harrell United States
Patrick Royston United Kingdom
Gary G. Koch United States
Peter C. Austin Canada
P. Armitage United Kingdom
Colin B. Begg United States
N. E. Breslow relative to Nan M. Laird United States Nan M. Laird's profile →
Citations per field
00.5×1.5×
Nan M. Laird · 1×
Citations per year

Countries citing papers authored by N. E. Breslow

Since Specialization
Citations

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

Fields of papers citing papers by N. E. Breslow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20150
2 201214
3 201023
4 200712
5 200131
6 20004
7 1998218
8 199846
9 199741
10 199631
11 199455
12 199433
13 19944
14 199183
15 199053
16 198833
17
Statistical methods in cancer research. IARC Workshop 25-27 May 1983.
1987100
18
ORGANIZATION AND ANALYSIS OF COMPARATIVE THERAPEUTIC ESSAIS INVOLVING EXTENSIVE SUPERVISION OF THE SICK
19790
19 197967
20 1978327

About N. E. Breslow

N. E. Breslow is a scholar working on Statistics and Probability, Pathology and Forensic Medicine and Demography, having authored 111 papers that have together received 40.1k indexed citations. Recurring topics across this work include Renal and related cancers (38 papers), Statistical Methods and Bayesian Inference (17 papers), Statistical Methods and Inference (15 papers), Renal cell carcinoma treatment (11 papers), Advanced Causal Inference Techniques (11 papers), Tumors and Oncological Cases (10 papers), Statistical Methods in Clinical Trials (8 papers) and Health Systems, Economic Evaluations, Quality of Life (7 papers). The work is most often cited by research in Statistics and Probability (8.0k citations), Oncology (6.1k citations) and Pathology and Forensic Medicine (3.6k citations). N. E. Breslow has collaborated with scholars based in United States, France and Sweden. Frequent co-authors include N. E. Day, David Clayton, D. R. Cox, David Oakes, Peter G. Smith, Nathan Mantel, Richard Peto, P. Armitage, Julian Peto and Kerri McPherson. Their work appears in journals such as Journal of Clinical Oncology, Biometrics, Journal of the American Statistical Association, American Journal of Epidemiology and JNCI Journal of the National Cancer Institute.

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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