Xiao‐Li Meng
Impact in
- Statistics and Probability top 0.02%
- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Artificial Intelligence top 0.2%
- Bayesian Methods and Mixture Models
Papers in
-
- Statistical Methods and Bayesian Inference 38
- Statistical Methods and Inference 32
- Advanced Statistical Methods and Models 14
- Markov Chains and Monte Carlo Methods 10
- Statistical Methods in Clinical Trials 8
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- Bayesian Methods and Mixture Models 25
- Co-authors
- Andrew Gelman (4 shared papers)Donald B. Rubin (6 shared papers)David A. van Dyk (9 shared papers)Hal S. Stern (1 shared paper)Galin L. Jones (2 shared papers)Steve Brooks (2 shared papers)Margarita Alegrı́a (8 shared papers)Wing Hung Wong (1 shared paper)
- Journals
- Journal of the American Statistical Association (9 papers)Journal of Computational and Graphical Statistics (7 papers)Statistical Science (7 papers)The Annals of Statistics (5 papers)The American Statistician (5 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Xiao‐Li Meng
109 papers receiving 12.9k citations
Xiao‐Li Meng's Hit Papers
Peers
Comparison fields: 5 of 225
- Statistics and Probability 4.6k
- Artificial Intelligence 3.3k
- Statistics, Probability and Uncertainty 691
- Clinical Psychology 1.7k
- Management Science and Operations Research 948
Countries citing papers authored by Xiao‐Li Meng
This map shows the geographic impact of Xiao‐Li Meng'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 Xiao‐Li Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao‐Li Meng more than expected).
Fields of papers citing papers by Xiao‐Li Meng
This network shows the impact of papers produced by Xiao‐Li Meng. 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 Xiao‐Li Meng. The network helps show where Xiao‐Li Meng may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiao‐Li Meng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Handbook of Markov Chain Monte Carlo Hit paper breakdown → | 2011 | 1852 |
| 2 | POSTERIOR PREDICTIVE ASSESSMENT OF MODEL FITNESS VIA REALIZED DISCREPANCIES Hit paper breakdown → | 1996 | 1469 |
| 3 | Maximum likelihood estimation via the ECM algorithm: A general framework Hit paper breakdown → | 1993 | 1196 |
| 4 | Prevalence of Mental Illness in Immigrant and Non-Immigrant U.S. Latino Groups Hit paper breakdown → | 2008 | 716 |
| 5 | The Art of Data Augmentation Hit paper breakdown → | 2001 | 713 |
| 6 | Factors affecting the detection of trends: Statistical considerations and applications to environmental data Hit paper breakdown → | 1998 | 668 |
| 7 | Simulating normalizing constants: from importance sampling to bridge sampling to path sampling Hit paper breakdown → | 1998 | 608 |
| 8 | Disparity in Depression Treatment Among Racial and Ethnic Minority Populations in the United States Hit paper breakdown → | 2008 | 574 |
| 9 | Posterior Predictive $p$-Values Hit paper breakdown → | 1994 | 558 |
| 10 | Multiple-Imputation Inferences with Uncongenial Sources of Input Hit paper breakdown → | 1994 | 539 |
| 11 | Considering context, place and culture: the National Latino and Asian American Study Hit paper breakdown → | 2004 | 530 |
| 12 | Disparity in Depression Treatment Among Racial and Ethnic Minority Populations in the United States Hit paper breakdown → | 2008 | 512 |
| 13 | 1997 | 494 | |
| 14 | SIMULATING RATIOS OF NORMALIZING CONSTANTS VIA A SIMPLE IDENTITY: A THEORETICAL EXPLORATION | 1996 | 400 |
| 15 | 1991 | 385 | |
| 16 | 1999 | 251 | |
| 17 | 1992 | 247 | |
| 18 | Significance levels from repeated p-values with multiply imputed data | 1991 | 190 |
| 19 | 2018 | 185 | |
| 20 | 2007 | 144 |
About Xiao‐Li Meng
Xiao‐Li Meng is a scholar working on Statistics and Probability, Artificial Intelligence, Management Science and Operations Research, Economics and Econometrics and Control and Systems Engineering, having authored 112 papers that have together received 13.8k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (38 papers), Statistical Methods and Inference (32 papers), Bayesian Methods and Mixture Models (25 papers), Advanced Statistical Methods and Models (14 papers), Markov Chains and Monte Carlo Methods (10 papers), Statistical Methods in Clinical Trials (8 papers), Multi-Criteria Decision Making (7 papers) and Optimization and Mathematical Programming (7 papers). The work is most often cited by research in Statistics and Probability (4.6k citations), Artificial Intelligence (3.3k citations), Statistics, Probability and Uncertainty (691 citations), Clinical Psychology (1.7k citations) and Management Science and Operations Research (948 citations). Xiao‐Li Meng has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Andrew Gelman, Donald B. Rubin, David A. van Dyk, Hal S. Stern, Galin L. Jones, Steve Brooks, Margarita Alegrı́a, Wing Hung Wong, David T. Takeuchi and Zhun Cao. Their work appears in journals such as Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Statistical Science, The Annals of Statistics and The American Statistician.
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.