Caroline Beunckens
- Statistics and Probability top 1%
- Health, Toxicology and Mutagenesis top 10%
- Molecular Biology
- Artificial Intelligence top 10%
- Physiology
- Co-authors
- Geert MolenberghsMichael G. KenwardCristina SottoGeert VerbekeCraig MallinckrodtCarl VaelStijn VerhulstKristine Desager
- Topics
- Statistical Methods and Bayesian Inference (14 papers)Statistical Methods and Inference (8 papers)Statistical Methods in Clinical Trials (7 papers)
- Cited by
- Statistics and ProbabilityHealth, Toxicology and MutagenesisNeuropsychology and Physiological Psychology
- Partner nations
- BelgiumUnited StatesPhilippines
In The Last Decade
Caroline Beunckens
17 papers receiving 773 citations
Peers
Comparison fields: 5 of 122
- Statistics and Probability 325
- Health, Toxicology and Mutagenesis 126
- Molecular Biology 104
- Artificial Intelligence 102
- Physiology 73
Countries citing papers authored by Caroline Beunckens
This map shows the geographic impact of Caroline Beunckens'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 Caroline Beunckens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Caroline Beunckens more than expected).
Fields of papers citing papers by Caroline Beunckens
This network shows the impact of papers produced by Caroline Beunckens. 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 Caroline Beunckens. The network helps show where Caroline Beunckens may publish in the future.
Co-authorship network of co-authors of Caroline Beunckens
This figure shows the co-authorship network connecting the top 25 collaborators of Caroline Beunckens. A scholar is included among the top collaborators of Caroline Beunckens 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 Caroline Beunckens. Caroline Beunckens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 82 | |
| 2 | Marginal correlation in longitudinal binary data based on generalized linear mixed models | 1 |
| 3 | 6 | |
| 4 | 4 | |
| 5 | 6 | |
| 6 | EVERY MISSING NOT AT RANDOM MODEL HAS GOT A MISSING AT RANDOM COUNTERPART WITH EQUAL FIT | 45 |
| 7 | 140 | |
| 8 | 56 | |
| 9 | 1 | |
| 10 | 151 | |
| 11 | 68 | |
| 12 | Analysis and Sensitivity Analysis for Incomplete Longitudinal Data | 1 |
| 13 | 13 | |
| 14 | 60 | |
| 15 | 12 | |
| 16 | 36 | |
| 17 | 128 |
About Caroline Beunckens
Caroline Beunckens is a scholar working on Statistics and Probability, Pharmacy and Statistics, Probability and Uncertainty, having authored 17 papers that have together received 810 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (14 papers), Statistical Methods and Inference (8 papers) and Statistical Methods in Clinical Trials (7 papers). The work is most often cited by research in Statistics and Probability (325 citations), Health, Toxicology and Mutagenesis (126 citations) and Neuropsychology and Physiological Psychology (7 citations). Caroline Beunckens has collaborated with scholars based in Belgium, United States and Philippines. Frequent co-authors include Geert Molenberghs, Michael G. Kenward, Cristina Sotto, Geert Verbeke, Craig Mallinckrodt, Carl Vael, Stijn Verhulst, Kristine Desager, Vera Nelen and Gudrun Koppen. Their work appears in journals such as American Journal of Clinical Nutrition, Biometrics and Environmental Health Perspectives.
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.