Bradley Saul

603 total citations
13 papers, 211 citations indexed

About

Bradley Saul is a scholar working on Statistics and Probability, Physiology and Hematology. According to data from OpenAlex, Bradley Saul has authored 13 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 3 papers in Physiology and 2 papers in Hematology. Recurrent topics in Bradley Saul's work include Advanced Causal Inference Techniques (5 papers), Statistical Methods and Bayesian Inference (3 papers) and Statistical Methods and Inference (3 papers). Bradley Saul is often cited by papers focused on Advanced Causal Inference Techniques (5 papers), Statistical Methods and Bayesian Inference (3 papers) and Statistical Methods and Inference (3 papers). Bradley Saul collaborates with scholars based in United States, United Kingdom and Denmark. Bradley Saul's co-authors include Michael G. Hudgens, John S. Finnell, Alan Goldhamer, Toshia R. Myers, Kelly Richardson, Craig McDougall, Mohammad Ali, Lan Liu, John D. Clemens and Leah J. McGrath and has published in prestigious journals such as Journal of the American Statistical Association, Clinical Pharmacology & Therapeutics and American Journal of Transplantation.

In The Last Decade

Bradley Saul

12 papers receiving 200 citations

Peers

Bradley Saul
Prosenjit Kundu United States
Chenghao Chu United States
Michelle Peters United States
H. Pan United Kingdom
Ida J. Spruill United States
Prosenjit Kundu United States
Bradley Saul
Citations per year, relative to Bradley Saul Bradley Saul (= 1×) peers Prosenjit Kundu

Countries citing papers authored by Bradley Saul

Since Specialization
Citations

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

Fields of papers citing papers by Bradley Saul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bradley Saul

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

All Works

13 of 13 papers shown
1.
Saul, Bradley, et al.. (2025). Sparsentan for Halting Renal Disease Progression in Transplant Recipients with Recurrent IgA Nephropathy. American Journal of Transplantation. 25(8). S779–S779.
3.
McGrath, Leah J., Carrie M. Nielson, Bradley Saul, et al.. (2021). Lessons Learned Using Real‐World Data to Emulate Randomized Trials: A Case Study of Treatment Effectiveness for Newly Diagnosed Immune Thrombocytopenia. Clinical Pharmacology & Therapeutics. 110(6). 1570–1578. 4 indexed citations
4.
Nielson, Carrie M., Alexander Breskin, Bradley Saul, et al.. (2021). Effectiveness and Safety of Romiplostim Among Patients with Newly Diagnosed, Persistent and Chronic Immune Thrombocytopenia in European Clinical Practice. Advances in Therapy. 38(5). 2673–2688. 11 indexed citations
5.
Reading, Stephanie, Bradley Saul, Leah J. McGrath, et al.. (2020). <p>Lipid Testing Trends in the US Before and After the Release of the 2013 Cholesterol Treatment Guidelines</p>. Clinical Epidemiology. Volume 12. 835–845. 2 indexed citations
6.
McGrath, Leah J., Leslie Spangler, Jeffrey R. Curtis, et al.. (2020). Using negative control outcomes to assess the comparability of treatment groups among women with osteoporosis in the United States. Pharmacoepidemiology and Drug Safety. 29(8). 854–863. 16 indexed citations
7.
Saul, Bradley & Michael G. Hudgens. (2020). The Calculus of M-Estimation in R with geex. Journal of Statistical Software. 92(2). 29 indexed citations
8.
Saul, Bradley, et al.. (2020). Doubly robust estimation in observational studies with partial interference. UNC Libraries. 1 indexed citations
9.
Saul, Bradley, Michael G. Hudgens, & Michael A. Mallin. (2019). Downstream Effects of Upstream Causes. Journal of the American Statistical Association. 114(528). 1493–1504. 7 indexed citations
10.
Liu, Lan, Michael G. Hudgens, Bradley Saul, et al.. (2019). Doubly robust estimation in observational studies with partial interference. Stat. 8(1). 17 indexed citations
11.
Finnell, John S., Bradley Saul, Alan Goldhamer, & Toshia R. Myers. (2018). Is fasting safe? A chart review of adverse events during medically supervised, water-only fasting. BMC Complementary and Alternative Medicine. 18(1). 67–67. 52 indexed citations
12.
Saul, Bradley & Michael G. Hudgens. (2017). A Recipe for inferference: Start with Causal Inference. Add Interference. Mix Well with R.. Journal of Statistical Software. 82(2). 13 indexed citations
13.
McDougall, Craig, et al.. (2014). Effects of 7 days on an ad libitum low-fat vegan diet: the McDougall Program cohort. Nutrition Journal. 13(1). 99–99. 53 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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