Klaus‐Peter Schulz

6.1k citations
14 papers · 4.9k indexed · 1 hit paper · h-index 10

Klaus‐Peter Schulz

13 papers receiving 4.7k citations

Hit Papers

Empirical evidence of bias. Dimensions of methodological ...4.6k199520262005201510002.0k3.0k4.0k

Peers

Klaus‐Peter Schulz
Comparison fields: 5 of 174
  • Statistics, Probability and Uncertainty 997
  • Complementary and alternative medicine 292
  • Statistics and Probability 287
  • Hepatology 244
  • Psychiatry and Mental health 392
Replace Ba’ Pham with:
Ba’ Pham Canada
Tianjing Li United States
David M. Rind United States
Romina Brignardello‐Petersen Canada
Bruno Giraudeau France
Harry Smith United States
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Karmela Krleža-Jerić Canada
Wendy R. Parulekar Canada
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Citations per year

Countries citing papers authored by Klaus‐Peter Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Klaus‐Peter Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Klaus‐Peter Schulz. 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 Klaus‐Peter Schulz. The network helps show where Klaus‐Peter Schulz may publish in the future.

Co-authorship network

The 14 scholars most cited alongside Klaus‐Peter Schulz, 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 Klaus‐Peter Schulz Line = papers co-authored together Klaus‐Peter Schulz links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20240
2 201810
3 20174
4 20169
5 201553
6 20127
7 201023
8 20101
9 200821
10 200651
11 200523
12 200354
13 200025
14
Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trialsbreakdown →
19954585

About Klaus‐Peter Schulz

Klaus‐Peter Schulz is a scholar working on Human Factors and Ergonomics, Toxicology, Organizational Behavior and Human Resource Management, Statistics, Probability and Uncertainty and Human-Computer Interaction, having authored 14 papers that have together received 4.9k indexed citations. Recurring topics across this work include Innovative Education and Learning Practices (5 papers), Sustainability in Higher Education (3 papers), Reproductive Health and Contraception (2 papers), Organizational Learning and Leadership (2 papers), Meta-analysis and systematic reviews (2 papers), Design Education and Practice (2 papers), Creativity in Education and Neuroscience (2 papers) and Molecular spectroscopy and chirality (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (997 citations), Complementary and alternative medicine (292 citations), Statistics and Probability (287 citations), Hepatology (244 citations) and Psychiatry and Mental health (392 citations). Klaus‐Peter Schulz has collaborated with scholars based in Germany, France and United States. Frequent co-authors include Morton E. Munk, Jens Krzywinski, Hubertus A.A.M. van Vliet, David A. Grimes, Laureen M Lopez, FM Helmerhorst, Hartmut Laatsch, Rajendra P. Maskey, Iris Grün-Wollny and Serge Fotso. Their work appears in journals such as Journal of Cleaner Production, The Journal of Antibiotics, JAMA, The Learning Organization and Creativity and Innovation Management.

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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