David Ohlssen

974 citations
32 papers · 655 · h-index 12

Impact in

Papers in

    • Statistical Methods in Clinical Trials 20
    • Statistical Methods and Inference 8
    • Advanced Causal Inference Techniques 7
    • Statistical Methods and Bayesian Inference 5
    • Statistics Education and Methodologies 2
    • Statistical Distribution Estimation and Applications 1
    • Optimal Experimental Design Methods 8

David Ohlssen

32 papers receiving 641 citations

Peers

David Ohlssen
Comparison fields: 5 of 108
  • Statistics and Probability 352
  • Statistics, Probability and Uncertainty 63
  • Economics and Econometrics 157
  • Management Science and Operations Research 63
  • Health Informatics 6
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Citations per field
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Citations per year

Countries citing papers authored by David Ohlssen

Since Specialization
Citations

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

Fields of papers citing papers by David Ohlssen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Ohlssen. 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 David Ohlssen. The network helps show where David Ohlssen may publish in the future.

Co-authors

The 25 scholars most cited alongside David Ohlssen, 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 David Ohlssen Line = papers co-authored together David Ohlssen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006126
2 201176
3 200772
4 200755
5 201352
6 201747
7 200737
8 201327
9 201323
10 201621
11 201319
12 201711
13 202110
14 202310
15 20209
16 20168
17 20227
18 20157
19 20155
20 20224

About David Ohlssen

David Ohlssen is a scholar working on Statistics and Probability, Management Science and Operations Research, Economics and Econometrics, Artificial Intelligence and Molecular Biology, having authored 32 papers that have together received 655 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (20 papers), Statistical Methods and Inference (8 papers), Optimal Experimental Design Methods (8 papers), Advanced Causal Inference Techniques (7 papers), Health Systems, Economic Evaluations, Quality of Life (7 papers), Statistical Methods and Bayesian Inference (5 papers), Statistics Education and Methodologies (2 papers) and Statistical Distribution Estimation and Applications (1 paper). The work is most often cited by research in Statistics and Probability (352 citations), Statistics, Probability and Uncertainty (63 citations), Economics and Econometrics (157 citations), Management Science and Operations Research (63 citations) and Health Informatics (6 citations). David Ohlssen has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include David J. Spiegelhalter, Linda Sharples, Hayley E. Jones, Heinz Schmidli, Beat Neuenschwander, Amy Racine, Michael Branson, Björn Bornkamp, Frank Bretz and Marc Vandemeulebroecke. Their work appears in journals such as Pharmaceutical Statistics, Statistics in Biopharmaceutical Research, Statistics in Medicine, Journal of Biopharmaceutical Statistics and Journal of the Royal Statistical Society Series C (Applied Statistics).

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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