Earl Duncan

825 total citations · 1 hit paper
18 papers, 611 citations indexed

About

Earl Duncan is a scholar working on Economics and Econometrics, Statistics and Probability and Oncology. According to data from OpenAlex, Earl Duncan has authored 18 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Economics and Econometrics, 6 papers in Statistics and Probability and 5 papers in Oncology. Recurrent topics in Earl Duncan's work include Statistical Methods and Bayesian Inference (6 papers), Spatial and Panel Data Analysis (6 papers) and demographic modeling and climate adaptation (5 papers). Earl Duncan is often cited by papers focused on Statistical Methods and Bayesian Inference (6 papers), Spatial and Panel Data Analysis (6 papers) and demographic modeling and climate adaptation (5 papers). Earl Duncan collaborates with scholars based in Australia, Indonesia and Netherlands. Earl Duncan's co-authors include Kerrie Mengersen, Morgan Pokorny, Fritz H. Schröder, Jelle O. Barentsz, Maarten de Rooij, L. C. Thompson, Susanna Cramb, Nicole White, Peter D. Baade and Joanne F. Aitken and has published in prestigious journals such as PLoS ONE, European Urology and International Journal of Environmental Research and Public Health.

In The Last Decade

Earl Duncan

17 papers receiving 601 citations

Hit Papers

Prospective Study of Diagnostic Accuracy Comparing Prosta... 2014 2026 2018 2022 2014 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Earl Duncan Australia 8 378 178 129 80 50 18 611
Paul R. Womble United States 10 344 0.9× 48 0.3× 35 0.3× 68 0.8× 39 0.8× 13 448
J.L. Domínguez-Escrig Spain 10 237 0.6× 68 0.4× 30 0.2× 23 0.3× 12 0.2× 28 493
H. Ballentine Carter United States 5 716 1.9× 187 1.1× 46 0.4× 43 0.5× 199 4.0× 6 861
Maximilian Peter Brandt Germany 12 167 0.4× 51 0.3× 42 0.3× 13 0.2× 11 0.2× 47 461
Jammbe Musoro Belgium 13 155 0.4× 14 0.1× 16 0.1× 61 0.8× 68 1.4× 27 533
Sung Hwi Hong South Korea 14 125 0.3× 27 0.2× 22 0.2× 31 0.4× 80 1.6× 27 582
Mark T. Corkum Canada 11 174 0.5× 13 0.1× 43 0.3× 12 0.1× 66 1.3× 36 354
Jean‐David Zeitoun France 15 63 0.2× 105 0.6× 14 0.1× 131 1.6× 65 1.3× 62 648
Jacqueline E. Livsey United Kingdom 12 329 0.9× 41 0.2× 150 1.2× 7 0.1× 24 0.5× 17 792
Nahila Justo Sweden 10 88 0.2× 25 0.1× 31 0.2× 62 0.8× 28 0.6× 21 418

Countries citing papers authored by Earl Duncan

Since Specialization
Citations

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

Fields of papers citing papers by Earl Duncan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Earl Duncan

This figure shows the co-authorship network connecting the top 25 collaborators of Earl Duncan. A scholar is included among the top collaborators of Earl Duncan 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 Earl Duncan. Earl Duncan 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.
Goodwin, Sarah, Thomas L. Saunders, Joanne F. Aitken, et al.. (2024). Designing the Australian Cancer Atlas: visualizing geostatistical model uncertainty for multiple audiences. Journal of the American Medical Informatics Association. 31(11). 2447–2454. 3 indexed citations
2.
Goodwin, Sarah, Thomas L. Saunders, Joanne F. Aitken, et al.. (2023). Table of Contents. 5–6. 1 indexed citations
3.
Cook, Dianne, et al.. (2023). A Hexagon Tile Map Algorithm for Displaying Spatial Data. The R Journal. 15(1). 6–16. 1 indexed citations
4.
Duncan, Earl, et al.. (2022). Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data. PLoS ONE. 17(5). e0268130–e0268130. 1 indexed citations
5.
Cramb, Susanna, et al.. (2021). Detecting Spatial Autocorrelation for a Small Number of Areas: a practical example. Journal of Physics Conference Series. 1899(1). 12098–12098. 16 indexed citations
6.
Cramb, Susanna, et al.. (2020). Evaluating the impact of a small number of areas on spatial estimation. International Journal of Health Geographics. 19(1). 39–39. 22 indexed citations
7.
Duncan, Earl & Kerrie Mengersen. (2020). Comparing Bayesian spatial models: Goodness-of-smoothing criteria for assessing under- and over-smoothing. PLoS ONE. 15(5). e0233019–e0233019. 17 indexed citations
8.
Duncan, Earl, et al.. (2020). Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics. International Journal of Health Geographics. 19(1). 42–42. 5 indexed citations
9.
Cramb, Susanna, et al.. (2020). Climate variability and dengue fever in Makassar, Indonesia: Bayesian spatio-temporal modelling. Spatial and Spatio-temporal Epidemiology. 33. 100335–100335. 20 indexed citations
10.
Cramb, Susanna, Earl Duncan, Joanne F. Aitken, et al.. (2020). Geographical patterns in melanoma incidence across Australia: can thickness differentials reveal the key drivers?. 4. 11–11. 6 indexed citations
11.
Duncan, Earl, et al.. (2020). Augmenting disease maps: a Bayesian meta-analysis approach. Royal Society Open Science. 7(8). 192151–192151. 4 indexed citations
12.
Cramb, Susanna, et al.. (2020). Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia. International Journal of Environmental Research and Public Health. 17(3). 878–878. 18 indexed citations
13.
Duncan, Earl, Susanna Cramb, Joanne F. Aitken, Kerrie Mengersen, & Peter D. Baade. (2019). Development of the Australian Cancer Atlas: spatial modelling, visualisation, and reporting of estimates. International Journal of Health Geographics. 18(1). 21–21. 28 indexed citations
14.
Cramb, Susanna, Earl Duncan, Peter D. Baade, & Kerrie Mengersen. (2018). Investigation of Bayesian spatial models. QUT ePrints (Queensland University of Technology). 6 indexed citations
15.
Duncan, Earl, Nicole White, & Kerrie Mengersen. (2017). Spatial smoothing in Bayesian models: a comparison of weights matrix specifications and their impact on inference. International Journal of Health Geographics. 16(1). 47–47. 64 indexed citations
16.
Duncan, Earl, Nicole White, & Kerrie Mengersen. (2016). Bayesian spatiotemporal modelling for identifying unusual and unstable trends in mammography utilisation. BMJ Open. 6(5). e010253–e010253. 3 indexed citations
17.
Cramb, Susanna, Earl Duncan, Nicole White, Peter D. Baade, & Kerrie Mengersen. (2016). Spatial Modelling Methods. QUT ePrints (Queensland University of Technology). 1 indexed citations
18.
Pokorny, Morgan, Maarten de Rooij, Earl Duncan, et al.. (2014). Prospective Study of Diagnostic Accuracy Comparing Prostate Cancer Detection by Transrectal Ultrasound–Guided Biopsy Versus Magnetic Resonance (MR) Imaging with Subsequent MR-guided Biopsy in Men Without Previous Prostate Biopsies. European Urology. 66(1). 22–29. 395 indexed citations breakdown →

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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