C. B. Dean

3.5k total citations
78 papers, 2.5k citations indexed

About

C. B. Dean is a scholar working on Statistics and Probability, Economics and Econometrics and Global and Planetary Change. According to data from OpenAlex, C. B. Dean has authored 78 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Statistics and Probability, 18 papers in Economics and Econometrics and 17 papers in Global and Planetary Change. Recurrent topics in C. B. Dean's work include Statistical Methods and Bayesian Inference (34 papers), Statistical Methods and Inference (19 papers) and Fire effects on ecosystems (15 papers). C. B. Dean is often cited by papers focused on Statistical Methods and Bayesian Inference (34 papers), Statistical Methods and Inference (19 papers) and Fire effects on ecosystems (15 papers). C. B. Dean collaborates with scholars based in Canada, United States and Spain. C. B. Dean's co-authors include Jerald F. Lawless, Jason D. Nielsen, Ying C. MacNab, Douglas G. Woolford, Stephen Taylor, David L. Martell, Gordon E. Willmot, Thorsten Wiegand, Stephan Getzin and J. A. Trofymow and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Technometrics.

In The Last Decade

C. B. Dean

74 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
C. B. Dean Canada	25	774	448	417	281	277	78	2.5k
John Hinde Ireland	25	1.1k 1.4×	214 0.5×	354 0.8×	528 1.9×	262 0.9×	68	3.8k
Daniel B. Hall United States	27	679 0.9×	321 0.7×	199 0.5×	269 1.0×	516 1.9×	79	2.8k
D. Stasinopoulos United Kingdom	15	828 1.1×	830 1.9×	372 0.9×	330 1.2×	269 1.0×	28	4.4k
Andrea Riebler Norway	17	399 0.5×	283 0.6×	389 0.9×	200 0.7×	180 0.6×	30	2.6k
Christopher Jackson United Kingdom	29	838 1.1×	183 0.4×	728 1.7×	357 1.3×	164 0.6×	86	4.0k
Robert A. Rigby United Kingdom	22	1.1k 1.4×	941 2.1×	456 1.1×	432 1.5×	325 1.2×	51	5.2k
Sara Martino Norway	13	811 1.0×	567 1.3×	681 1.6×	558 2.0×	416 1.5×	28	3.9k
Ding‐Geng Chen United States	27	366 0.5×	328 0.7×	136 0.3×	116 0.4×	235 0.8×	199	2.5k
Sigrunn H. Sørbye Norway	11	329 0.4×	291 0.6×	343 0.8×	195 0.7×	219 0.8×	33	1.8k
Louis‐Paul Rivest Canada	26	1.4k 1.9×	778 1.7×	646 1.5×	469 1.7×	225 0.8×	130	4.3k

Countries citing papers authored by C. B. Dean

Since Specialization

Citations

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

Fields of papers citing papers by C. B. Dean

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. B. Dean. 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 C. B. Dean. The network helps show where C. B. Dean may publish in the future.

Co-authorship network of co-authors of C. B. Dean

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

All Works

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20 of 20 papers shown

Dean, C. B., et al.. (2025). Learning associations of COVID-19 hospitalizations with wastewater viral signals by Markov modulated models. Epidemics. 52. 100840–100840.

Renouf, Elizabeth, et al.. (2023). An exploration of the relationship between wastewater viral signals and COVID-19 hospitalizations in Ottawa, Canada. Infectious Disease Modelling. 8(3). 617–631. 9 indexed citations

Woolford, Douglas G., et al.. (2022). Wildland fire prevention: the impact of the Modifying Industrial Operations Protocol on the growth of industrial forestry-caused wildland fires in Ontario, Canada. International Journal of Wildland Fire. 31(9). 825–834. 5 indexed citations

Woolford, Douglas G., et al.. (2022). A Case-Crossover Study of the Impact of the Modifying Industrial Operations Protocol on the Frequency of Industrial Forestry-Caused Wildland Fires in Ontario, Canada. Journal of Agricultural Biological and Environmental Statistics. 28(2). 219–242. 2 indexed citations

Woolford, Douglas G., et al.. (2022). On the selection of an interpolation method with an application to the Fire Weather Index in Ontario, Canada. Environmetrics. 34(2). 6 indexed citations

Woolford, Douglas G., et al.. (2020). Algorithmically deconstructing shot locations as a method for shot quality in hockey. Journal of Quantitative Analysis in Sports. 17(2). 107–115.

Dean, C. B., et al.. (2016). Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards. Statistics in Biosciences. 9(2). 622–645. 2 indexed citations

Juarez‐Colunga, Elizabeth & C. B. Dean. (2013). Analysis of Repeated Events and Panel Count Data. Boletín de la Sociedad Matemática Mexicana. 19(2). 309–318. 1 indexed citations

Nepomnaschy, Pablo A., et al.. (2012). Who is stressed? Comparing cortisol levels between individuals. American Journal of Human Biology. 24(4). 515–525. 21 indexed citations

10.

Cooper, Peter, et al.. (2007). Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown. Journal of Safety Research. 38(1). 25–33. 11 indexed citations

11.

Nathoo, Farouk S. & C. B. Dean. (2007). A Mixed Mover–Stayer Model for Spatiotemporal Two‐State Processes. Biometrics. 63(3). 881–891. 5 indexed citations

12.

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

13.

MacNab, Ying C. & C. B. Dean. (2002). Spatio‐temporal modelling of rates for the construction of disease maps. Statistics in Medicine. 21(3). 347–358. 56 indexed citations

14.

Balshaw, Robert & C. B. Dean. (2002). A Semiparametric Model for the Analysis of Recurrent-Event Panel Data. Biometrics. 58(2). 324–331. 8 indexed citations

15.

Militino, Ana F., M. D. Ugarte, & C. B. Dean. (2001). The use of mixture models for identifying high risks in disease mapping. Statistics in Medicine. 20(13). 2035–2049. 28 indexed citations

16.

MacNab, Ying C. & C. B. Dean. (2001). Autoregressive Spatial Smoothing and Temporal Spline Smoothing for Mapping Rates. Biometrics. 57(3). 949–956. 77 indexed citations

17.

Dean, C. B., M. D. Ugarte, & Ana F. Militino. (2001). Detecting Interaction Between Random Region and Fixed Age Effects in Disease Mapping. Biometrics. 57(1). 197–202. 59 indexed citations

18.

Dean, C. B., et al.. (2001). Simultaneous modelling of operative mortality and long‐term survival after coronary artery bypass surgery. Statistics in Medicine. 20(13). 1931–1945. 9 indexed citations

19.

MacNab, Ying C. & C. B. Dean. (2000). Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models. Statistics in Medicine. 19(17-18). 2421–2435. 44 indexed citations

20.

Dean, C. B.. (1994). Modified pseudo-likelihood estimator of the overdispersion parameter in Poisson mixture models. Journal of Applied Statistics. 21(6). 523–532. 22 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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