Joie Ensor
About
Joie Ensor is a scholar working on Statistics, Probability and Uncertainty, Economics and Econometrics and Statistics and Probability.
According to data from OpenAlex, Joie Ensor has authored 66 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Statistics, Probability and Uncertainty, 20 papers in Economics and Econometrics and 19 papers in Statistics and Probability. Recurrent topics in Joie Ensor's work include Meta-analysis and systematic reviews (31 papers), Health Systems, Economic Evaluations, Quality of Life (17 papers) and Statistical Methods in Clinical Trials (11 papers). Joie Ensor is often cited by papers focused on Meta-analysis and systematic reviews (31 papers), Health Systems, Economic Evaluations, Quality of Life (17 papers) and Statistical Methods in Clinical Trials (11 papers). Joie Ensor collaborates with scholars based in United Kingdom, Netherlands and United States. Joie Ensor's co-authors include Richard D Riley, Kym I E Snell, Gary S. Collins, Karel G.M. Moons, Frank E. Harrell, Thomas P. A. Debray, Danielle Burke, Johannes B. Reitsma, Maarten van Smeden and Glen P. Martin and has published in prestigious journals such as PLoS ONE, Scientific Reports and BMJ.
In The Last Decade
Joie Ensor
61 papers receiving 5.0k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Joie Ensor United Kingdom | 25 | 963 | 931 | 841 | 532 | 503 | 66 | 5.1k | ||
| Kym I E Snell United Kingdom | 27 | 1.1k 1.1× | 979 1.1× | 847 1.0× | 588 1.1× | 562 1.1× | 73 | 5.3k | ||
| Thomas P. A. Debray Netherlands | 40 | 951 1.0× | 1.1k 1.2× | 1.1k 1.3× | 555 1.0× | 735 1.5× | 108 | 6.4k | ||
| Maarten van Smeden Netherlands | 37 | 939 1.0× | 1.2k 1.3× | 931 1.1× | 635 1.2× | 1.1k 2.1× | 139 | 6.9k | ||
| Joris A. H. de Groot Netherlands | 25 | 667 0.7× | 798 0.9× | 487 0.6× | 579 1.1× | 329 0.7× | 39 | 4.2k | ||
| Nirav R. Shah United States | 32 | 709 0.7× | 717 0.8× | 628 0.7× | 436 0.8× | 205 0.4× | 128 | 6.0k | ||
| Rumana Omar United Kingdom | 43 | 741 0.8× | 818 0.9× | 1.6k 1.9× | 658 1.2× | 187 0.4× | 126 | 6.9k | ||
| Karel G. M. Moons Netherlands | 16 | 679 0.7× | 551 0.6× | 665 0.8× | 469 0.9× | 276 0.5× | 33 | 3.3k | ||
| Matthew Sperrin United Kingdom | 37 | 641 0.7× | 695 0.7× | 1.1k 1.3× | 645 1.2× | 468 0.9× | 161 | 4.4k | ||
| Geert J. M. G. van der Heijden Netherlands | 47 | 2.9k 3.0× | 1.4k 1.6× | 886 1.1× | 747 1.4× | 283 0.6× | 190 | 9.2k | ||
| Robert Wolff United Kingdom | 27 | 1.0k 1.0× | 1.1k 1.1× | 499 0.6× | 876 1.6× | 326 0.6× | 96 | 6.6k |
Countries citing papers authored by Joie Ensor
Since
Specialization
Citations
This map shows the geographic impact of Joie Ensor'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 Joie Ensor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joie Ensor more than expected).
Fields of papers citing papers by Joie Ensor
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Joie Ensor. 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 Joie Ensor. The network helps show where Joie Ensor may publish in the future.
Co-authorship network of co-authors of Joie Ensor
This figure shows the co-authorship network connecting the top 25 collaborators of Joie Ensor. A scholar is included among the top collaborators of Joie Ensor 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 Joie Ensor. Joie Ensor is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Riley, Richard D, Gary S. Collins, Kym I E Snell, et al.. (2025). Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches. BMJ. 388. e080749–e080749.
2.
Martin, Glen P., Richard D Riley, Joie Ensor, & Stuart W Grant. (2025). Statistical primer: sample size considerations for developing and validating clinical prediction models. European Journal of Cardio-Thoracic Surgery. 67(5).
3.
Whittle, Rebecca, Joie Ensor, Lucinda Archer, et al.. (2025). Extended sample size calculations for evaluation of prediction models using a threshold for classification. BMC Medical Research Methodology. 25(1). 170–170.
4.
Riley, Richard D, Gary S. Collins, Lucinda Archer, et al.. (2025). A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models — part 2: time-to-event outcomes. PubMed. 9(1). 33–33.
5.
Riley, Richard D, Joie Ensor, Kym I E Snell, et al.. (2025). Importance of sample size on the quality and utility of AI-based prediction models for healthcare. The Lancet Digital Health. 7(6). 100857–100857.
6.
Riley, Richard D, Lucinda Archer, Kym I E Snell, et al.. (2024). Evaluation of clinical prediction models (part 2): how to undertake an external validation study. BMJ. 384. e074820–e074820.
7.
Crocker, Thomas F, Natalie Lam, Joie Ensor, et al.. (2024). Development of the Community-based complex Interventions to sustain Independence in Older People (CII-OP) typology: a qualitative synthesis of interventions in randomised controlled trials. Age and Ageing. 53(5).
8.
Archer, Lucinda, et al.. (2023). Using temporal recalibration to improve the calibration of risk prediction models in competing risk settings when there are trends in survival over time. Statistics in Medicine. 42(27). 5007–5024.
9.
Crocker, Thomas F, Natalie Lam, Joie Ensor, et al.. (2023). 1600 COMMUNITY-BASED COMPLEX INTERVENTIONS TO SUSTAIN INDEPENDENCE IN OLDER PEOPLE: SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS. Age and Ageing. 52(Supplement_2).
10.
Riley, Richard D, et al.. (2023). Two‐stage or not two‐stage? That is the question for IPD meta‐analysis projects. Research Synthesis Methods. 14(6). 903–910.
11.
Crocker, Thomas F, Natalie Lam, Caroline Brundle, et al.. (2023). Risk-of-bias assessment using Cochrane's revised tool for randomized trials (RoB 2) was useful but challenging and resource-intensive: observations from a systematic review. Journal of Clinical Epidemiology. 161. 39–45.
12.
Levis, Brooke, Kym I E Snell, Johanna AAG Damen, et al.. (2023). Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. Journal of Clinical Epidemiology. 165. 111206–111206.
13.
Riley, Richard D, Gary S. Collins, Joie Ensor, et al.. (2021). Minimum sample size calculations for external validation of a clinical prediction model with a time‐to‐event outcome. Statistics in Medicine. 41(7). 1280–1295.
14.
Snell, Kym I E, Lucinda Archer, Joie Ensor, et al.. (2021). External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb. Journal of Clinical Epidemiology. 135. 79–89.
15.
Riley, Richard D, Thomas P. A. Debray, David J. Fisher, et al.. (2020). Individual participant data meta‐analysis to examine interactions between treatment effect and participant‐level covariates: Statistical recommendations for conduct and planning. Statistics in Medicine. 39(15). 2115–2137.
16.
Riley, Richard D, Karel G.M. Moons, Kym I E Snell, et al.. (2019). A guide to systematic review and meta-analysis of prognostic factor studies. BMJ. 364. k4597–k4597.
17.
Riley, Richard D, Kym I E Snell, Joie Ensor, et al.. (2018). Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes. Statistics in Medicine. 38(7). 1276–1296.
18.
Burke, Danielle, Joie Ensor, Kym I E Snell, Daniëlle van der Windt, & Richard D Riley. (2017). Guidance for deriving and presenting percentage study weights in meta‐analysis of test accuracy studies. Research Synthesis Methods. 9(2). 163–178.
19.
Snell, Kym I E, Thomas P. A. Debray, Joie Ensor, et al.. (2015). Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model. Journal of Clinical Epidemiology. 69. 40–50.
20.
Ensor, Joie, et al.. (1992). Ethical issues related to chemical dependency.. PubMed. 38(4). 85, 87–85, 87.
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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