Math J. J. M. Candel

155 papers receiving 4.9k citations

Peers

Math J. J. M. Candel
Comparison fields: 5 of 187
  • Applied Psychology 998
  • Tourism, Leisure and Hospitality Management 102
  • Statistics and Probability 399
  • General Health Professions 1.1k
  • Public Health, Environmental and Occupational Health 1.2k
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Citations per year

Countries citing papers authored by Math J. J. M. Candel

Since Specialization
Citations

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

Fields of papers citing papers by Math J. J. M. Candel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Math J. J. M. Candel. 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 Math J. J. M. Candel. The network helps show where Math J. J. M. Candel may publish in the future.

Co-authors

The 25 scholars most cited alongside Math J. J. M. Candel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Math J. J. M. Candel Line = papers co-authored together Math J. J. M. Candel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 162 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993348
2 2001221
3 2007168
4 2006160
5 2020159
6 2006159
7 2010147
8 2004123
9 2021108
10 2012106
11 2006104
12 2014101
13 200591
14 200989
15 200683
16 201280
17 199979
18 200774
19 200969
20 200463

About Math J. J. M. Candel

Math J. J. M. Candel is a scholar working on Applied Psychology, Physiology, Statistics and Probability, General Health Professions and Public Health, Environmental and Occupational Health, having authored 162 papers that have together received 5.1k indexed citations. Recurring topics across this work include Behavioral Health and Interventions (47 papers), Smoking Behavior and Cessation (37 papers), Statistical Methods and Bayesian Inference (19 papers), Statistical Methods in Clinical Trials (19 papers), Obesity, Physical Activity, Diet (18 papers), Health Systems, Economic Evaluations, Quality of Life (14 papers), Advanced Causal Inference Techniques (14 papers) and School Health and Nursing Education (10 papers). The work is most often cited by research in Applied Psychology (998 citations), Tourism, Leisure and Hospitality Management (102 citations), Statistics and Probability (399 citations), General Health Professions (1.1k citations) and Public Health, Environmental and Occupational Health (1.2k citations). Math J. J. M. Candel has collaborated with scholars based in Netherlands, Taiwan and United States. Frequent co-authors include Hein de Vries, Gerard van Breukelen, Nanné K. de Vries, Liesbeth Mercken, Stef Kremers, Jascha de Nooijer, Martijn P. F. Berger, Evelien Reinaerts, Koert van Ittersum and Liesbeth van Osch. Their work appears in journals such as Journal of Medical Internet Research, Nicotine & Tobacco Research, Statistics in Medicine, Statistical Methods in Medical Research and BMC Public Health.

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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