L. J. Wei

17.9k total citations · 7 hit papers
123 papers, 13.1k citations indexed

About

L. J. Wei is a scholar working on Statistics and Probability, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, L. J. Wei has authored 123 papers receiving a total of 13.1k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Statistics and Probability, 17 papers in Economics and Econometrics and 11 papers in Management Science and Operations Research. Recurrent topics in L. J. Wei's work include Statistical Methods and Inference (50 papers), Statistical Methods and Bayesian Inference (38 papers) and Statistical Methods in Clinical Trials (33 papers). L. J. Wei is often cited by papers focused on Statistical Methods and Inference (50 papers), Statistical Methods and Bayesian Inference (38 papers) and Statistical Methods in Clinical Trials (33 papers). L. J. Wei collaborates with scholars based in United States, Japan and Spain. L. J. Wei's co-authors include D. Y. Lin, Z. Ying, Lisa A. Weissfeld, Tianxi Cai, Lü Tian, Hajime Uno, Ralph B. D’Agostino, Michael Pencina, Sen Cheng and Ilsoon Yang and has published in prestigious journals such as Physical Review Letters, Circulation and Journal of Clinical Oncology.

In The Last Decade

L. J. Wei

118 papers receiving 12.7k citations

Hit Papers

The Robust Inference for the Cox Proportional Hazards Model 1989 2026 2001 2013 1989 1989 1993 2011 2000 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The Robust Inference for the Cox Proportional Hazards Model
    1989 2.1k citations L. J. Wei et al. Journal of the American Statistical Association profile →
  2. Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions
    1989 1.4k citations L. J. Wei et al. Journal of the American Statistical Association profile →
  3. Checking the Cox model with cumulative sums of martingale-based residuals
    1993 1.2k citations L. J. Wei, Z. Ying et al. profile →
  4. On the C‐statistics for evaluating overall adequacy of risk prediction procedures with censored survival data
    2011 978 citations Hajime Uno, L. J. Wei et al. Statistics in Medicine profile →
  5. Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
    2000 647 citations L. J. Wei, Z. Ying et al. profile →
  6. The accelerated failure time model: A useful alternative to the cox regression model in survival analysis
    1992 534 citations L. J. Wei Statistics in Medicine profile →
  7. Moving Beyond the Hazard Ratio in Quantifying the Between-Group Difference in Survival Analysis
    2014 421 citations Hajime Uno, Brian Claggett et al. Journal of Clinical Oncology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. J. Wei United States 49 5.7k 1.4k 1.3k 1.0k 1.0k 123 13.1k
D. Y. Lin United States 50 6.1k 1.1× 2.3k 1.6× 1.3k 1.0× 1.1k 1.0× 889 0.9× 146 15.0k
Thomas A. Louis United States 57 4.0k 0.7× 1.7k 1.2× 1.1k 0.8× 769 0.7× 1.4k 1.4× 242 15.2k
Niels Keiding Denmark 63 4.7k 0.8× 1.2k 0.8× 1.0k 0.8× 1.1k 1.0× 1.0k 1.0× 266 20.0k
Xiao‐Hua Zhou United States 64 2.9k 0.5× 1.2k 0.8× 1.6k 1.3× 1.1k 1.1× 1.7k 1.6× 540 17.1k
Kung‐Yee Liang United States 36 2.9k 0.5× 1.2k 0.9× 1.8k 1.4× 897 0.9× 596 0.6× 87 15.7k
Vernon T. Farewell United Kingdom 72 2.5k 0.4× 1.2k 0.8× 1.4k 1.1× 1.7k 1.7× 634 0.6× 287 18.5k
John P. Klein United States 67 3.8k 0.7× 1.3k 0.9× 1.3k 1.1× 1.7k 1.7× 718 0.7× 279 21.6k
Anastasios A. Tsiatis United States 60 7.8k 1.4× 1.8k 1.3× 735 0.6× 483 0.5× 914 0.9× 161 12.2k
Sander Greenland United States 50 3.0k 0.5× 1.3k 0.9× 1.8k 1.4× 1.0k 1.0× 273 0.3× 88 14.6k
Margaret S. Pepe United States 57 4.9k 0.9× 1.2k 0.8× 2.0k 1.6× 1.6k 1.5× 1.7k 1.7× 155 20.2k

Countries citing papers authored by L. J. Wei

Since Specialization
Citations

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

Fields of papers citing papers by L. J. Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. J. Wei

This figure shows the co-authorship network connecting the top 25 collaborators of L. J. Wei. A scholar is included among the top collaborators of L. J. Wei 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 L. J. Wei. L. J. Wei 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.
LaRowe, Lisa R., et al.. (2024). Prevalence and Sociodemographic Correlates of Chronic Pain Among a Nationally Representative Sample of Older Adults in the United States. Journal of Pain. 25(10). 104614–104614. 8 indexed citations
2.
Huang, Bo, et al.. (2024). Inferences for the distribution of the duration of response in a comparative clinical study. Clinical Trials. 21(5). 541–552.
3.
Skali, Hicham, et al.. (2024). Pitfalls of Choosing a Study End Point Including Cardiovascular Death in Comparative Clinical Trials. Circulation. 150(23). 1823–1825. 3 indexed citations
4.
LaRowe, Lisa R., Christine Miaskowski, Francis J. Keefe, et al.. (2023). Chronic Pain and Pain Management in Older Adults. Nursing Research. 73(1). 81–88. 1 indexed citations
5.
McCaw, Zachary R., Dae Hyun Kim, & L. J. Wei. (2022). Pitfall in the Design and Analysis of Comparative Oncology Trials With a Time-to-Event Endpoint and Recommendations. JNCI Cancer Spectrum. 6(1). 4 indexed citations
6.
McCaw, Zachary R., Lü Tian, Dae Hyun Kim, A. Russell Localio, & L. J. Wei. (2020). Survival Analysis of Treatment Efficacy in Comparative Coronavirus Disease 2019 Studies. Clinical Infectious Diseases. 72(11). e887–e889. 3 indexed citations
7.
Tian, Lü, Hua Jin, Hajime Uno, et al.. (2020). On the empirical choice of the time window for restricted mean survival time. Biometrics. 76(4). 1157–1166. 58 indexed citations
8.
Uno, Hajime, Brian Claggett, Lü Tian, et al.. (2014). Moving Beyond the Hazard Ratio in Quantifying the Between-Group Difference in Survival Analysis. Journal of Clinical Oncology. 32(22). 2380–2385. 421 indexed citations breakdown →
9.
Claggett, Brian, Lü Tian, Davide Castagno, & L. J. Wei. (2014). Treatment selections using risk-benefit profiles based on data from comparative randomized clinical trials with multiple endpoints. Biostatistics. 16(1). 60–72. 29 indexed citations
10.
Li, Yi, Lü Tian, & L. J. Wei. (2010). Estimating Subject-Specific Dependent Competing Risk Profile with Censored Event Time Observations. Biometrics. 67(2). 427–435. 8 indexed citations
11.
Li, Lingling, Scott Evans, Hajime Uno, & L. J. Wei. (2009). Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials. Statistics in Biopharmaceutical Research. 1(4). 348–355. 13 indexed citations
12.
Zhou, Huanyu, L. J. Wei, Xiping Xu, & Xin Xu. (2007). Combining Association Tests across Multiple Genetic Markers in Case-Control Studies. Human Heredity. 65(3). 166–174. 1 indexed citations
13.
Wang, Lin, Yan Feng, Yan Zhang, et al.. (2006). Prolylcarboxypeptidase gene, chronic hypertension, and risk of preeclampsia. American Journal of Obstetrics and Gynecology. 195(1). 162–171. 54 indexed citations
14.
Lin, D. Y., L. J. Wei, & Z. Ying. (2002). Model‐Checking Techniques Based on Cumulative Residuals. Biometrics. 58(1). 1–12. 224 indexed citations
15.
Glidden, David V. & L. J. Wei. (1999). Rank Estimation of Treatment Differences Based on Repeated Measurements Subject to Dependent Censoring. Journal of the American Statistical Association. 94(447). 888–895. 7 indexed citations
16.
Wei, L. J., et al.. (1997). ANALYSIS OF REPEATED VIROLOGICAL MEASUREMENTS BASED ON CELL DILUTION ASSAYS. Statistics in Medicine. 16(5). 571–582. 2 indexed citations
17.
Ying, Z., Sin‐Ho Jung, & L. J. Wei. (1995). Survival Analysis with Median Regression Models. Journal of the American Statistical Association. 90(429). 178–184. 230 indexed citations
18.
Zhang, Ying & L. J. Wei. (1994). The Kaplan-Meier Estimate for Dependent Failure Time Observations. Journal of Multivariate Analysis. 50(1). 17–29. 100 indexed citations
19.
Su, John Q. & L. J. Wei. (1991). A Lack-of-Fit Test for the Mean Function in a Generalized Linear Model. Journal of the American Statistical Association. 86(414). 420–426. 91 indexed citations
20.
Stram, Daniel O., L. J. Wei, & James H. Ware. (1988). Analysis of Repeated Ordered Categorical Outcomes with Possibly Missing Observations and Time-Dependent Covariates. Journal of the American Statistical Association. 83(403). 631–637. 85 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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