Helena Geys
- Statistics and Probability top 0.5%
- Economics and Econometrics top 2%
- Oncology top 10%
- Molecular Biology
- Management Science and Operations Research top 5%
- Co-authors
- Geert MolenberghsDidier RenardMarc BuyseTomasz BurzykowskiTony VangeneugdenMarc AertsLouise RyanAriel Alonso
- Topics
- Statistical Methods in Clinical Trials (36 papers)Statistical Methods and Bayesian Inference (36 papers)Optimal Experimental Design Methods (21 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
- Partner nations
- BelgiumUnited StatesUnited Kingdom
In The Last Decade
Helena Geys
88 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 163
- Statistics and Probability 944
- Economics and Econometrics 406
- Oncology 240
- Molecular Biology 210
- Management Science and Operations Research 187
Countries citing papers authored by Helena Geys
This map shows the geographic impact of Helena Geys'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 Helena Geys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Helena Geys more than expected).
Fields of papers citing papers by Helena Geys
This network shows the impact of papers produced by Helena Geys. 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 Helena Geys. The network helps show where Helena Geys may publish in the future.
Co-authorship network of co-authors of Helena Geys
This figure shows the co-authorship network connecting the top 25 collaborators of Helena Geys. A scholar is included among the top collaborators of Helena Geys 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 Helena Geys. Helena Geys is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 11 | |
| 3 | 8 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 53 | |
| 8 | 12 | |
| 9 | Modelling Combined Continuous and Ordinal Outcomes from Developmental Toxicity Studies | 1 |
| 10 | Marginal correlation in longitudinal binary data based on generalized linear mixed models | 1 |
| 11 | 6 | |
| 12 | 13 | |
| 13 | 2 | |
| 14 | 93 | |
| 15 | 60 | |
| 16 | 46 | |
| 17 | Analysis of clustered binary data with covariates specific to each observation | 43 |
| 18 | 8 | |
| 19 | 428 | |
| 20 | 10 |
About Helena Geys
Helena Geys is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 93 papers that have together received 2.1k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (36 papers), Statistical Methods and Bayesian Inference (36 papers) and Optimal Experimental Design Methods (21 papers). The work is most often cited by research in Statistics and Probability (944 citations), Statistics, Probability and Uncertainty (114 citations) and Management Science and Operations Research (187 citations). Helena Geys has collaborated with scholars based in Belgium, United States and United Kingdom. Frequent co-authors include Geert Molenberghs, Didier Renard, Marc Buyse, Tomasz Burzykowski, Tony Vangeneugden, Marc Aerts, Louise Ryan, Ariel Alonso, Christel Faes and Annouschka Laenen. Their work appears in journals such as Journal of the American Statistical Association, Biometrics and International Journal of Cancer.
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.