R. L. Prentice

2.8k total citations
33 papers, 1.7k citations indexed

About

R. L. Prentice is a scholar working on Statistics and Probability, Public Health, Environmental and Occupational Health and Oncology. According to data from OpenAlex, R. L. Prentice has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 5 papers in Public Health, Environmental and Occupational Health and 4 papers in Oncology. Recurrent topics in R. L. Prentice's work include Statistical Methods and Bayesian Inference (7 papers), Statistical Methods and Inference (7 papers) and Statistical Distribution Estimation and Applications (6 papers). R. L. Prentice is often cited by papers focused on Statistical Methods and Bayesian Inference (7 papers), Statistical Methods and Inference (7 papers) and Statistical Distribution Estimation and Applications (6 papers). R. L. Prentice collaborates with scholars based in United States, South Africa and Australia. R. L. Prentice's co-authors include J. Cai, Ziding Feng, Li Hsu, C. Y. Wang, David V. Glidden, Thomas R. Fleming, Margaret S. Pepe, S. L. Gorbach, David M. Thompson and David P. Byar and has published in prestigious journals such as Journal of Clinical Oncology, Journal of the American Statistical Association and Blood.

In The Last Decade

R. L. Prentice

32 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
R. L. Prentice United States 16 837 355 232 203 157 33 1.7k
Thomas Louis United States 18 344 0.4× 239 0.7× 440 1.9× 116 0.6× 117 0.7× 28 2.1k
Geert Schou Denmark 25 143 0.2× 185 0.5× 415 1.8× 146 0.7× 117 0.7× 41 1.7k
Andrea Burton United Kingdom 16 457 0.5× 133 0.4× 224 1.0× 86 0.4× 27 0.2× 26 1.4k
Daowen Zhang United States 23 737 0.9× 231 0.7× 44 0.2× 351 1.7× 60 0.4× 50 1.9k
Gregg E. Dinse United States 21 547 0.7× 76 0.2× 132 0.6× 85 0.4× 42 0.3× 57 1.4k
Vanessa Didelez Germany 23 817 1.0× 162 0.5× 60 0.3× 756 3.7× 158 1.0× 77 2.3k
Joseph S. Koopmeiners United States 28 305 0.4× 251 0.7× 273 1.2× 190 0.9× 474 3.0× 109 2.2k
Marian R. Fisher United States 15 206 0.2× 341 1.0× 116 0.5× 133 0.7× 228 1.5× 19 4.0k
Lei Nie United States 22 659 0.8× 66 0.2× 545 2.3× 113 0.6× 49 0.3× 72 2.0k
Myron Chang United States 33 467 0.6× 607 1.7× 722 3.1× 294 1.4× 48 0.3× 126 3.4k

Countries citing papers authored by R. L. Prentice

Since Specialization
Citations

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

Fields of papers citing papers by R. L. Prentice

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. L. Prentice. 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 R. L. Prentice. The network helps show where R. L. Prentice may publish in the future.

Co-authorship network of co-authors of R. L. Prentice

This figure shows the co-authorship network connecting the top 25 collaborators of R. L. Prentice. A scholar is included among the top collaborators of R. L. Prentice based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with R. L. Prentice. R. L. Prentice is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Prentice, R. L.. (2024). Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values. Journal of the American Statistical Association. 119(548). 3184–3186. 2 indexed citations
2.
Yang, Song & R. L. Prentice. (2010). Estimation of the 2-sample hazard ratio function using a semiparametric model. Biostatistics. 12(2). 354–368. 10 indexed citations
3.
Prentice, R. L., Pamela A. Shaw, Sheila Bingham, et al.. (2009). Biomarker-calibrated Energy and Protein Consumption and Increased Cancer Risk Among Postmenopausal Women. American Journal of Epidemiology. 169(8). 977–989. 75 indexed citations
4.
Chlebowski, Rowan T., Tomáš Rohan, Deanna L. Lane, et al.. (2004). Ethnicity and breast cancer in the Women's Health Initiative: A unifying concept for unfavorable outcome in African American women. Journal of Clinical Oncology. 22(14_suppl). 1008–1008. 2 indexed citations
5.
Prentice, R. L.. (2001). Methodologic challenges in chronic disease population research. Biostatistics. 2(4). 365–381. 8 indexed citations
6.
McCombe, Pamela, Robert J. Wilson, & R. L. Prentice. (2000). Results of testing for anti-GM1 antibodies. Journal of Clinical Neuroscience. 7(3). 209–212. 13 indexed citations
7.
Fan, Juanjuan, Li Hsu, & R. L. Prentice. (2000). Dependence Estimation Over a Finite Bivariate Failure Time Region. Lifetime Data Analysis. 6(4). 343–355. 32 indexed citations
8.
Prentice, R. L.. (1999). On non-parametric maximum likelihood estimation of the bivariate survivor function. Statistics in Medicine. 18(17-18). 2517–2527. 5 indexed citations
9.
Wang, C. Y., Li Hsu, Ziding Feng, & R. L. Prentice. (1997). Regression Calibration in Failure Time Regression. Biometrics. 53(1). 131–131. 122 indexed citations
10.
Zhao, Lue Ping, et al.. (1997). Population–based family study designs: An interdisciplinary research framework for genetic epidemiology. Genetic Epidemiology. 14(4). 365–388. 5 indexed citations
11.
Prentice, R. L.. (1995). On the role, design, and analysis of disease prevention trials. Controlled Clinical Trials. 16(4). 249–258. 1 indexed citations
12.
Fleming, Thomas R., R. L. Prentice, Margaret S. Pepe, & David V. Glidden. (1994). Surrogate and auxiliary endpoints in clinical trials, with potential applications in cancer and aids research. Statistics in Medicine. 13(9). 955–968. 119 indexed citations
13.
Freedman, L. S., R. L. Prentice, Corinne Clifford, et al.. (1993). Dietary Fat and Breast Cancer: Where We Are. JNCI Journal of the National Cancer Institute. 85(10). 764–765. 33 indexed citations
14.
Zhao, Lue Ping, Lawrence H. Kushi, Russell D. Klein, & R. L. Prentice. (1991). Quantitative review of studies of dietary fat and rat colon carcinoma. Nutrition and Cancer. 15(3-4). 169–177. 42 indexed citations
15.
Prentice, R. L., et al.. (1990). Dietary Fat Reduction and Plasma Estradiol Concentration in Healthy Postmenopausal Women. JNCI Journal of the National Cancer Institute. 82(2). 129–134. 146 indexed citations
16.
Miller, Anthony B., R. L. Prentice, Robert Tibshirani, Norman F. Boyd, & Paul Corey. (1989). Terry fox cancer research workshop on prevention trials. International Journal of Cancer. 44(5). 767–769. 1 indexed citations
17.
Prentice, R. L.. (1982). Covariate Measurement Errors and Parameter Estimation in a Failure Time Regression Model. Biometrika. 69(2). 331–331. 14 indexed citations
18.
Prentice, R. L.. (1978). Linear Rank Tests with Right Censored Data. Biometrika. 65(1). 167–167. 33 indexed citations
19.
Storb, R, PL Weiden, R. L. Prentice, et al.. (1977). Aplastic anemia (AA) treated by allogeneic marrow transplantation: the Seattle experience.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 9(1). 181–5. 8 indexed citations
20.
Prentice, R. L.. (1973). Exponential survivals with censoring and explanatory variables. Biometrika. 60(2). 279–288. 158 indexed citations

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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