Kellyn F Arnold

1.6k total citations · 1 hit paper
19 papers, 888 citations indexed

About

Kellyn F Arnold is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Kellyn F Arnold has authored 19 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 6 papers in Artificial Intelligence and 4 papers in Economics and Econometrics. Recurrent topics in Kellyn F Arnold's work include Advanced Causal Inference Techniques (9 papers), COVID-19 epidemiological studies (3 papers) and Geochemistry and Geologic Mapping (3 papers). Kellyn F Arnold is often cited by papers focused on Advanced Causal Inference Techniques (9 papers), COVID-19 epidemiological studies (3 papers) and Geochemistry and Geologic Mapping (3 papers). Kellyn F Arnold collaborates with scholars based in United Kingdom, Netherlands and United States. Kellyn F Arnold's co-authors include Mark S. Gilthorpe, Peter W. G. Tennant, Georgia D Tomova, Laurie Berrie, Eleanor J. Murray, Wendy J. Harrison, George T. H. Ellison, Lynsie R Ranker, Matthew P. Fox and Sarah Gadd and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and American Journal of Clinical Nutrition.

In The Last Decade

Kellyn F Arnold

18 papers receiving 879 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

2020 534 citations Peter W. G. Tennant, Eleanor J. Murray et al. International Journal of Epidemiology profile →

Peers

Kellyn F Arnold

PHEOH

PPCH

PHYSI

Georgia D Tomova United Kingdom

Claire Keeble United Kingdom

Lynsie R Ranker United States

Sarah Gadd United Kingdom

Laurie Berrie United Kingdom

Emily M. Mitchell United States

Tra My Pham United Kingdom

Barbra A. Dickerman United States

D. Leann Long United States

Amal Saki Malehi Iran

Georgia D Tomova United Kingdom

Kellyn F Arnold

158 ×0.9

PHEOH

84 ×0.7

70 ×0.8

75 ×0.9

PPCH

80 ×1.0

PHYSI

Citations per year, relative to Kellyn F Arnold Kellyn F Arnold (= 1×) peers Georgia D Tomova

Countries citing papers authored by Kellyn F Arnold

Since Specialization

Citations

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

Fields of papers citing papers by Kellyn F Arnold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kellyn F Arnold. 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 Kellyn F Arnold. The network helps show where Kellyn F Arnold may publish in the future.

Co-authorship network of co-authors of Kellyn F Arnold

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Stokes, Jonathan, Andreas Höhn, Marc de Kamps, et al.. (2025). Simulating hierarchical data to assess the utility of ecological versus multilevel analyses in obtaining individual-level causal effects. BMC Medical Research Methodology. 25(1). 79–79. 2 indexed citations

Touma, Zahi, Ian N Bruce, Richard Furie, et al.. (2025). Reduced organ damage accumulation in adult patients with SLE on anifrolumab plus standard of care compared to real-world external controls. Annals of the Rheumatic Diseases. 84(5). 767–776. 1 indexed citations

Tsang, Carmen, et al.. (2025). Characteristics, Treatment Patterns, and Outcomes of Patients with Multiple Myeloma, Including Those Who are Triple‐Class Exposed: A Retrospective Cohort Study in England Using National Cancer Registry Data. eJHaem. 6(4). e70064–e70064.

Berrie, Laurie, Kellyn F Arnold, Georgia D Tomova, Mark S. Gilthorpe, & Peter W. G. Tennant. (2024). Depicting deterministic variables within directed acyclic graphs: an aid for identifying and interpreting causal effects involving derived variables and compositional data. American Journal of Epidemiology. 194(2). 469–479. 7 indexed citations

Arnold, Kellyn F, et al.. (2024). Application of the target trial emulation framework to external comparator studies. SHILAP Revista de lepidopterología. 4. 1380568–1380568. 3 indexed citations

Wilson‐Aggarwal, Jared K., Kellyn F Arnold, Moira Spyer, et al.. (2023). Assessing spatiotemporal variability in SARS-CoV-2 infection risk for hospital workers using routinely-collected data. PLoS ONE. 18(4). e0284512–e0284512. 1 indexed citations

Berrie, Laurie, Kellyn F Arnold, Georgia D Tomova, Mark S. Gilthorpe, & Peter W. G. Tennant. (2023). OP112 Depicting deterministic variables within directed acyclic graphs (DAGs): An aid for identifying and interpreting causal effects involving compositional data and composite variables. A55–A55. 3 indexed citations

Arnold, Kellyn F, Mark S. Gilthorpe, Nisreen A Alwan, et al.. (2022). Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study. PLoS ONE. 17(4). e0263432–e0263432. 9 indexed citations

Tennant, Peter W. G., Georgia D Tomova, Kellyn F Arnold, & Mark S. Gilthorpe. (2022). OP09 Lord’s ‘paradox’ explained: The 50-year warning on the analyses of ‘change scores’*. A5.1–A5. 2 indexed citations

10.

Tomova, Georgia D, Kellyn F Arnold, Mark S. Gilthorpe, & Peter W. G. Tennant. (2021). Adjustment for energy intake in nutritional research: a causal inference perspective. American Journal of Clinical Nutrition. 115(1). 189–198. 84 indexed citations

11.

Arnold, Kellyn F, et al.. (2020). Reflection on modern methods: generalized linear models for prognosis and intervention—theory, practice and implications for machine learning. International Journal of Epidemiology. 49(6). 2074–2082. 41 indexed citations

12.

Tennant, Peter W. G., Eleanor J. Murray, Kellyn F Arnold, et al.. (2020). Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. International Journal of Epidemiology. 50(2). 620–632. 534 indexed citations breakdown →

13.

Wilkinson, Jack, Kellyn F Arnold, Eleanor J. Murray, et al.. (2020). Time to reality check the promises of machine learning-powered precision medicine. The Lancet Digital Health. 2(12). e677–e680. 125 indexed citations

14.

Arnold, Kellyn F, Laurie Berrie, Peter W. G. Tennant, & Mark S. Gilthorpe. (2020). A causal inference perspective on the analysis of compositional data. International Journal of Epidemiology. 49(4). 1307–1313. 28 indexed citations

15.

Arnold, Kellyn F, et al.. (2019). OP78 A causal inference perspective on compositional data and collider ‘bias’. Oral Presentations. A38.2–A39. 3 indexed citations

16.

Tennant, Peter W. G., et al.. (2019). OP112 Use of outcome ‘change-scores’ in observational data are a potential source of inferential bias. Oral Presentations. A53.1–A53. 1 indexed citations

17.

Arnold, Kellyn F, George T. H. Ellison, Johannes Textor, et al.. (2018). Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges. Statistical Methods in Medical Research. 28(5). 1347–1364. 2 indexed citations

18.

Arnold, Kellyn F, Wendy J. Harrison, Alison Heppenstall, & Mark S. Gilthorpe. (2018). DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference. International Journal of Epidemiology. 48(1). 243–253. 36 indexed citations

19.

Tennant, Peter W. G., et al.. (2017). Advanced Modelling Strategies: Challenges and pitfalls in robust causal inference with observational data. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 6 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.

Explore authors with similar magnitude of impact