Ming‐Wen An

498 total citations
12 papers, 355 citations indexed

About

Ming‐Wen An is a scholar working on Statistics and Probability, Cancer Research and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ming‐Wen An has authored 12 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistics and Probability, 4 papers in Cancer Research and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ming‐Wen An's work include Statistical Methods and Bayesian Inference (4 papers), Advanced Causal Inference Techniques (3 papers) and Cancer Genomics and Diagnostics (3 papers). Ming‐Wen An is often cited by papers focused on Statistical Methods and Bayesian Inference (4 papers), Advanced Causal Inference Techniques (3 papers) and Cancer Genomics and Diagnostics (3 papers). Ming‐Wen An collaborates with scholars based in United States, Belgium and China. Ming‐Wen An's co-authors include F. Javier Nieto, Daniel J. Buysse, Anne B. Newman, Mark L. Unruh, Susan Redline, Constantine Frangakis, Donald B. Rubin, Ellen J. MacKenzie, Brian Caffo and Charles A. Rohde and has published in prestigious journals such as Journal of Clinical Oncology, JNCI Journal of the National Cancer Institute and Biometrics.

In The Last Decade

Ming‐Wen An

12 papers receiving 346 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming‐Wen An United States 7 178 97 64 48 40 12 355
E. Clay France 13 45 0.3× 24 0.2× 9 0.1× 55 1.1× 48 1.2× 61 522
Tulsi Adhikari India 13 85 0.5× 61 0.6× 4 0.1× 36 0.8× 85 2.1× 39 396
Clair Blacketer United States 10 51 0.3× 18 0.2× 8 0.1× 60 1.3× 40 1.0× 20 368
Gracinda de Sousa Portugal 8 41 0.2× 37 0.4× 11 0.2× 11 0.2× 47 1.2× 17 273
Tom Tenhave United States 8 22 0.1× 11 0.1× 50 0.8× 89 1.9× 29 0.7× 9 456
Alison G. Hoffnagle United States 5 56 0.3× 15 0.2× 12 0.2× 90 1.9× 35 0.9× 6 413
Yosra Z. Ali Saudi Arabia 13 176 1.0× 86 0.9× 54 1.1× 93 2.3× 25 504
Simon Jackson Australia 13 104 0.6× 77 0.8× 9 0.1× 10 0.2× 12 0.3× 31 593
Lawrence Johnson United States 8 131 0.7× 152 1.6× 20 0.3× 20 0.4× 4 0.1× 11 428
Feinstein Ar United States 10 14 0.1× 13 0.1× 27 0.4× 56 1.2× 19 0.5× 30 387

Countries citing papers authored by Ming‐Wen An

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Wen An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Wen An. 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 Ming‐Wen An. The network helps show where Ming‐Wen An may publish in the future.

Co-authorship network of co-authors of Ming‐Wen An

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Wen An. A scholar is included among the top collaborators of Ming‐Wen An 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 Ming‐Wen An. Ming‐Wen An is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Ou, Fang‐Shu, et al.. (2021). Modeling tumor measurement data to predict overall survival (OS) in cancer clinical trials. Contemporary Clinical Trials Communications. 23. 100827–100827. 2 indexed citations
2.
3.
An, Ming‐Wen, Xinxin Dong, Jeffrey P. Meyers, et al.. (2015). Evaluating Continuous Tumor Measurement-Based Metrics as Phase II Endpoints for Predicting Overall Survival. JNCI Journal of the National Cancer Institute. 107(11). djv239–djv239. 16 indexed citations
4.
An, Ming‐Wen, Constantine Frangakis, & Constantin T. Yiannoutsos. (2014). Choosing profile double‐sampling designs for survival estimation with application to President's Emergency Plan for AIDS Relief evaluation. Statistics in Medicine. 33(12). 2017–2029. 4 indexed citations
5.
Mandrekar, Sumithra J., et al.. (2013). Multitrial evaluation of longitudinal tumor measurement (TM)-based metrics for predicting overall survival (OS) using the RECIST 1.1 data warehouse.. Journal of Clinical Oncology. 31(15_suppl). 6520–6520. 1 indexed citations
6.
Mandrekar, Sumithra J., Ming‐Wen An, & Daniel J. Sargent. (2012). A phase II trial design with direct assignment option for initial marker validation.. Journal of Clinical Oncology. 30(30_suppl). 34–34. 1 indexed citations
7.
Crawford, Stephen, Nicholas G Reich, Ming‐Wen An, et al.. (2008). Regional and temporal variation in American Red Cross blood donations, 1995 to 2005. Transfusion. 48(8). 1576–1583. 24 indexed citations
8.
An, Ming‐Wen, Constantine Frangakis, Beverly Musick, & Constantin T. Yiannoutsos. (2008). The Need for Double‐Sampling Designs in Survival Studies: An Application to Monitor PEPFAR. Biometrics. 65(1). 301–306. 21 indexed citations
9.
Unruh, Mark L., Susan Redline, Ming‐Wen An, et al.. (2008). Subjective and Objective Sleep Quality and Aging in the Sleep Heart Health Study. Journal of the American Geriatrics Society. 56(7). 1218–1227. 202 indexed citations
10.
Frangakis, Constantine, Donald B. Rubin, Ming‐Wen An, & Ellen J. MacKenzie. (2007). Principal Stratification Designs to Estimate Input Data Missing Due to Death. Biometrics. 63(3). 641–649. 40 indexed citations
11.
Caffo, Brian, Ming‐Wen An, & Charles A. Rohde. (2006). Flexible random intercept models for binary outcomes using mixtures of normals. Computational Statistics & Data Analysis. 51(11). 5220–5235. 24 indexed citations
12.
Caffo, Brian, Ming‐Wen An, & Charles A. Rohde. (2006). A FLEXIBLE GENERAL CLASS OF MARGINAL AND CONDITIONAL RANDOM INTERCEPT MODELS FOR BINARY OUTCOMES USING MIXTURES OF NORMALS. Collection of Biostatistics Research Archive. 1 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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