Guobing Lu

3.5k total citations · 3 hit papers
18 papers, 2.6k citations indexed

About

Guobing Lu is a scholar working on Statistics and Probability, Economics and Econometrics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Guobing Lu has authored 18 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics and Probability, 10 papers in Economics and Econometrics and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in Guobing Lu's work include Health Systems, Economic Evaluations, Quality of Life (9 papers), Statistical Methods in Clinical Trials (7 papers) and Meta-analysis and systematic reviews (6 papers). Guobing Lu is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (9 papers), Statistical Methods in Clinical Trials (7 papers) and Meta-analysis and systematic reviews (6 papers). Guobing Lu collaborates with scholars based in United Kingdom, Netherlands and Brazil. Guobing Lu's co-authors include A. E. Ades, Nicky J. Welton, Alex J. Sutton, Sofia Dias, Deborah M Caldwell, Gert van Valkenhoef, Bert de Brock, Hans L. Hillege, Nicola J. Cooper and Keith R. Abrams and has published in prestigious journals such as Journal of the American Statistical Association, Statistics in Medicine and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

Guobing Lu

18 papers receiving 2.6k citations

Hit Papers

Assessing Evidence Inconsistency in Mixed Treatment Compa... 2006 2026 2012 2019 2006 2012 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guobing Lu United Kingdom 15 571 437 377 361 308 18 2.6k
Jessica Barrett United Kingdom 23 384 0.7× 366 0.8× 657 1.7× 488 1.4× 412 1.3× 67 3.9k
G. Lu United Kingdom 10 781 1.4× 645 1.5× 725 1.9× 496 1.4× 492 1.6× 13 4.6k
Annabel Barrett United Kingdom 12 256 0.4× 195 0.4× 248 0.7× 207 0.6× 167 0.5× 17 1.8k
Dinah Reitman United States 11 877 1.5× 222 0.5× 594 1.6× 261 0.7× 343 1.1× 13 3.0k
Julie Pildal Denmark 9 526 0.9× 187 0.4× 324 0.9× 197 0.5× 434 1.4× 13 2.0k
Gernot Wassmer Germany 27 197 0.3× 1.1k 2.5× 479 1.3× 405 1.1× 222 0.7× 80 3.8k
Hubert J. A. Schouten Netherlands 28 212 0.4× 269 0.6× 345 0.9× 218 0.6× 510 1.7× 62 2.9k
Stephen Rice United Kingdom 23 89 0.2× 63 0.1× 635 1.7× 306 0.8× 297 1.0× 75 2.3k
Jayne Berrier United States 7 488 0.9× 118 0.3× 229 0.6× 94 0.3× 183 0.6× 8 1.5k
Bo Freyschuss Sweden 14 170 0.3× 32 0.1× 599 1.6× 308 0.9× 305 1.0× 27 2.7k

Countries citing papers authored by Guobing Lu

Since Specialization
Citations

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

Fields of papers citing papers by Guobing Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guobing Lu. 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 Guobing Lu. The network helps show where Guobing Lu may publish in the future.

Co-authorship network of co-authors of Guobing Lu

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

All Works

18 of 18 papers shown
1.
Thom, Howard, Ian R. White, Nicky J. Welton, & Guobing Lu. (2018). Automated methods to test connectedness and quantify indirectness of evidence in network meta‐analysis. Research Synthesis Methods. 10(1). 113–124. 20 indexed citations
2.
Ades, A. E., Guobing Lu, Sofia Dias, Evan Mayo‐Wilson, & Daphne Kounali. (2015). Simultaneous synthesis of treatment effects and mapping to a common scale: an alternative to standardisation. Research Synthesis Methods. 6(1). 96–107. 16 indexed citations
3.
Lu, Guobing, Daphne Kounali, & A. E. Ades. (2014). Simultaneous Multioutcome Synthesis and Mapping of Treatment Effects to a Common Scale. Value in Health. 17(2). 280–287. 17 indexed citations
4.
Dias, Sofia, Nicky J. Welton, Alex J. Sutton, et al.. (2014). Inconsistency in Networks of Evidence Based on Randomised Controlled Trials. 13 indexed citations
5.
Ades, A. E., Guobing Lu, & Jason Madan. (2013). Which Health-Related Quality-of-Life Outcome When Planning Randomized Trials: Disease-Specific or Generic, or Both? A Common Factor Model. Value in Health. 16(1). 185–194. 14 indexed citations
6.
Dias, Sofia, Nicky J. Welton, Alex J. Sutton, et al.. (2013). Evidence Synthesis for Decision Making 4. Medical Decision Making. 33(5). 641–656. 562 indexed citations breakdown →
7.
Achana, Felix, Nicola J. Cooper, Sofia Dias, et al.. (2012). Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta‐analysis to network meta‐analysis. Statistics in Medicine. 32(5). 752–771. 46 indexed citations
8.
Lu, Guobing, John Brazier, & A. E. Ades. (2012). Mapping from Disease-Specific to Generic Health-Related Quality-of-Life Scales: A Common Factor Model. Value in Health. 16(1). 177–184. 24 indexed citations
9.
Valkenhoef, Gert van, Guobing Lu, Bert de Brock, et al.. (2012). Automating network meta‐analysis. Research Synthesis Methods. 3(4). 285–299. 577 indexed citations breakdown →
10.
Lu, Guobing, Nicky J. Welton, Julian P. T. Higgins, Ian R. White, & A. E. Ades. (2011). Linear inference for mixed treatment comparison meta-analysis: A two-stage approach. Research Synthesis Methods. 2(1). 43–60. 60 indexed citations
11.
Dias, Sofia, Nicky J. Welton, Alex J. Sutton, et al.. (2011). NICE DSU Technical Support Document 4: Inconsistency in Networks of Evidence Based on Randomised Controlled Trials.. Bristol Research (University of Bristol). 169 indexed citations
12.
Critchley, Frank, et al.. (2009). A relaxed approach to combinatorial problems in robustness and diagnostics. Statistics and Computing. 20(1). 99–115. 6 indexed citations
13.
Ades, A. E., Nicky J. Welton, Deborah M Caldwell, et al.. (2008). Multiparameter evidence synthesis in epidemiology and medical decision-making. Journal of Health Services Research & Policy. 13(3_suppl). 12–22. 38 indexed citations
14.
Cooper, Nicola J., Alex J. Sutton, Guobing Lu, & Kamlesh Khunti. (2006). Mixed Comparison of Stroke Prevention Treatments in Individuals With Nonrheumatic Atrial Fibrillation. Archives of Internal Medicine. 166(12). 1269–1269. 110 indexed citations
15.
Ades, A. E., Mark Sculpher, Alex J. Sutton, et al.. (2006). Bayesian Methods for Evidence Synthesis in Cost-Effectiveness Analysis. PharmacoEconomics. 24(1). 1–19. 341 indexed citations
16.
Lu, Guobing & A. E. Ades. (2006). Assessing Evidence Inconsistency in Mixed Treatment Comparisons. Journal of the American Statistical Association. 101(474). 447–459. 591 indexed citations breakdown →
17.
Critchley, Frank, et al.. (2001). Influence Analysis Based on the Case Sensitivity Function. Journal of the Royal Statistical Society Series B (Statistical Methodology). 63(2). 307–323. 17 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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