Paul Gustafson

6.5k total citations
194 papers, 3.6k citations indexed

About

Paul Gustafson is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Paul Gustafson has authored 194 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 117 papers in Statistics and Probability, 32 papers in Economics and Econometrics and 26 papers in Artificial Intelligence. Recurrent topics in Paul Gustafson's work include Statistical Methods and Bayesian Inference (76 papers), Statistical Methods and Inference (54 papers) and Advanced Causal Inference Techniques (43 papers). Paul Gustafson is often cited by papers focused on Statistical Methods and Bayesian Inference (76 papers), Statistical Methods and Inference (54 papers) and Advanced Causal Inference Techniques (43 papers). Paul Gustafson collaborates with scholars based in Canada, United States and United Kingdom. Paul Gustafson's co-authors include Lawrence C. McCandless, Helen Tremlett, Mohammad Ehsanul Karim, John Petkau, Adrian R. Levy, Ying C. MacNab, Yinshan Zhao, Elaine Kingwell, Afsaneh Shirani and Charity Evans and has published in prestigious journals such as JAMA, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Paul Gustafson

182 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul Gustafson Canada 31 1.5k 491 429 370 317 194 3.6k
Cyrus R. Mehta United States 38 2.1k 1.3× 509 1.0× 652 1.5× 362 1.0× 248 0.8× 137 8.5k
Shaun R. Seaman United Kingdom 27 1.2k 0.8× 373 0.8× 703 1.6× 297 0.8× 410 1.3× 91 5.2k
Odd O. Aalen Norway 38 2.6k 1.7× 802 1.6× 542 1.3× 666 1.8× 134 0.4× 121 6.4k
Mei‐Ling Ting Lee United States 29 878 0.6× 237 0.5× 253 0.6× 338 0.9× 154 0.5× 103 5.2k
Bahjat F. Qaqish United States 36 1.0k 0.7× 269 0.5× 527 1.2× 301 0.8× 330 1.0× 121 5.2k
Christopher Jackson United Kingdom 29 838 0.5× 728 1.5× 418 1.0× 357 1.0× 91 0.3× 86 4.0k
Issa J Dahabreh United States 43 603 0.4× 557 1.1× 735 1.7× 186 0.5× 438 1.4× 155 7.3k
Arthur V. Peterson United States 34 1.2k 0.8× 425 0.9× 383 0.9× 246 0.7× 258 0.8× 80 5.1k
Jon Wakefield United States 41 1.0k 0.7× 505 1.0× 566 1.3× 432 1.2× 75 0.2× 133 5.4k
Tomasz Burzykowski Belgium 42 1.6k 1.1× 960 2.0× 364 0.8× 156 0.4× 459 1.4× 195 6.6k

Countries citing papers authored by Paul Gustafson

Since Specialization
Citations

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

Fields of papers citing papers by Paul Gustafson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Gustafson

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Gustafson. A scholar is included among the top collaborators of Paul Gustafson 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 Paul Gustafson. Paul Gustafson 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.
Sadatsafavi, Mohsen, et al.. (2026). Bayesian Sample Size Calculations for External Validation Studies of Risk Prediction Models. Statistics in Medicine. 45(3-5). e70389–e70389.
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Karim, Mohammad Ehsanul, Paul Gustafson, Jason M. Sutherland, et al.. (2024). The misclassification of depression and anxiety disorders in the multiple sclerosis prodrome: A probabilistic bias analysis. Annals of Epidemiology. 101. 67–73.
6.
Slater, Justin, et al.. (2023). A Bayesian approach to estimating COVID-19 incidence and infection fatality rates. Biostatistics. 25(2). 354–384. 1 indexed citations
7.
Campbell, Harlan & Paul Gustafson. (2022). Bayes Factors and Posterior Estimation: Two Sides of the Very Same Coin. The American Statistician. 77(3). 248–258. 1 indexed citations
8.
Gustafson, Paul, Bruce C. Allen, Annette M. Bachand, et al.. (2022). Is the cholesterol-perfluoroalkyl substance association confounded by dietary fiber intake?: a Bayesian analysis of NHANES data with adjustment for measurement error in fiber intake. Environmental Health. 21(1). 114–114. 2 indexed citations
9.
Danzer, Alexander M., Valentijn M. T. de Jong, Harlan Campbell, et al.. (2022). Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies. Journal of Clinical Epidemiology. 145. 29–38. 2 indexed citations
10.
Matthay, Ellicott C., Valentijn M. T. de Jong, Harlan Campbell, et al.. (2021). Current trends in the application of causal inference methods to pooled longitudinal observational infectious disease studies—A protocol for a methodological systematic review. PLoS ONE. 16(4). e0250778–e0250778. 3 indexed citations
11.
Liu, Yan, et al.. (2020). Investigating the Performance of Propensity Score Approaches for Differential Item Functioning Analysis. Human Biology. 18(1). 2–26. 2 indexed citations
12.
Burstyn, Igor, Francesco Barone‐Adesi, Frank de Vocht, & Paul Gustafson. (2019). What to Do When Accumulated Exposure Affects Health but Only Its Duration Was Measured? A Case of Linear Regression. International Journal of Environmental Research and Public Health. 16(11). 1896–1896. 3 indexed citations
13.
Gilbert, Mark, et al.. (2016). An assessment of population-based screening guidelines versus clinical prediction rules for chlamydia and gonorrhea case finding. Preventive Medicine. 89. 51–56. 4 indexed citations
14.
Islam, Md. Nazrul, Mel Krajden, Jean Shoveller, et al.. (2016). Impact of drug use and opioid substitution therapy on hepatitis C reinfection: The BC Hepatitis Testers Cohort. Hepatology. 63. 4 indexed citations
15.
Gustafson, Paul. (2012). Double-Robust Estimators: Slightly More Bayesian than Meets the Eye?. The International Journal of Biostatistics. 8(2). 1–15. 4 indexed citations
16.
Wang, Dongxu, et al.. (2012). Partial Identification arising from Nondifferential Exposure Misclassification: How Informative are Data on the Unlikely, Maybe, and Likely Exposed?. The International Journal of Biostatistics. 8(1). 31–31. 4 indexed citations
17.
Lefebvre, Geneviève & Paul Gustafson. (2010). Impact of Outcome Model Misspecification on Regression and Doubly-Robust Inverse Probability Weighting to Estimate Causal Effect. The International Journal of Biostatistics. 6(2). Article 15–Article 15. 5 indexed citations
18.
Gustafson, Paul. (2010). Bayesian Inference for Partially Identified Models. The International Journal of Biostatistics. 6(2). Article 17–Article 17. 36 indexed citations
19.
Gustafson, Paul & S. Siddarth. (2007). Describing the Dynamics of Attention to TV Commercials: A Hierarchical Bayes Analysis of the Time to Zap an Ad. Journal of Applied Statistics. 34(5). 585–609. 18 indexed citations
20.
Synnes, Anne, Ying C. MacNab, Zhenguo Qiu, et al.. (2006). Neonatal Intensive Care Unit Characteristics Affect the Incidence of Severe Intraventricular Hemorrhage. Medical Care. 44(8). 754–759. 71 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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