Beat Neuenschwander

3.7k citations
44 papers · 2.4k indexed · 1 hit paper · h-index 22

Beat Neuenschwander

44 papers receiving 2.3k citations

Hit Papers

Use of historical control data for assessing treatment ef...3272013202620172021100200300

Peers

Beat Neuenschwander
Comparison fields: 5 of 154
  • Statistics and Probability 1.5k
  • Statistics, Probability and Uncertainty 314
  • Management Science and Operations Research 450
  • Virology 97
  • Economics and Econometrics 545
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Citations per field
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Joseph F. Heyse · 1×
Citations per year

Countries citing papers authored by Beat Neuenschwander

Since Specialization
Citations

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

Fields of papers citing papers by Beat Neuenschwander

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20245
2 2016127
3 201689
4 201123
5 201018
6 2009129
7 200963
8 2008260
9 200224
10 200012
11 20008
12
Trends in the prevalence of infection with mycobacterium tuberculosis in Korea from 1965 to 1995: an analysis of seven surveys by mixture models.
200034
13 200073
14 199824
15 19986
16 19962
17 199631
18 19961
19 199518
20 199248

About Beat Neuenschwander

Beat Neuenschwander is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 44 papers that have together received 2.4k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (22 papers), Meta-analysis and systematic reviews (9 papers), Health Systems, Economic Evaluations, Quality of Life (8 papers), Optimal Experimental Design Methods (8 papers), Advanced Causal Inference Techniques (7 papers), Statistical Methods and Bayesian Inference (5 papers), Statistical Methods and Inference (4 papers) and Tuberculosis Research and Epidemiology (3 papers). The work is most often cited by research in Statistics and Probability (1.5k citations), Statistics, Probability and Uncertainty (314 citations) and Management Science and Operations Research (450 citations). Beat Neuenschwander has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Michael Branson, David J. Spiegelhalter, Satrajit Roychoudhury, Simon Wandel, Thomas Gsponer, Heinz Schmidli, Gorana Capkun-Niggli, Tim Friede, Christian Röver and Sandro Gsteiger. Their work appears in journals such as American Journal of Epidemiology, Biometrics and Methods in enzymology on CD-ROM/Methods in enzymology.

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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