Mark Simmonds

13.5k citations
67 papers · 6.8k indexed · 5 hit papers · h-index 29

Mark Simmonds

66 papers receiving 6.7k citations

Hit Papers

A comparison of heterogeneity variance estimators in simu...64120152026201820224008001.2k

Peers

Mark Simmonds
Comparison fields: 5 of 190
  • Statistics, Probability and Uncertainty 699
  • Public Health, Environmental and Occupational Health 2.0k
  • Pharmacy 284
  • Statistics and Probability 432
  • Obstetrics and Gynecology 349
Replace Suhail A.R. Doi with:
Suhail A.R. Doi Australia
Norma Terrin United States
Yu‐Kang Tu Taiwan
Stephen J. Walters United Kingdom
Mark Helfand United States
Diana R Elbourne United Kingdom
Ben Vandermeer Canada
Karla Hemming United Kingdom
Ralf Bender Germany
Sally Kerry United Kingdom
Mark Simmonds relative to Suhail A.R. Doi Australia Suhail A.R. Doi's profile →
Citations per field
00.5×1.5×2.2×
Suhail A.R. Doi · 1×
Citations per year

Countries citing papers authored by Mark Simmonds

Since Specialization
Citations

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

Fields of papers citing papers by Mark Simmonds

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20246
2 20242
3 20232
4 20226
5 20214
6 202123
7 202036
8 201921
9 201818
10
A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analysesbreakdown →
2018641
11 20178
12 201765
13 20164
14 201570
15 201521
16 2010191
17 201098
18 2007125
19 2006135
20 19993

About Mark Simmonds

Mark Simmonds is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Obstetrics and Gynecology, having authored 67 papers that have together received 6.8k indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (17 papers), Health Systems, Economic Evaluations, Quality of Life (8 papers), Statistical Methods in Clinical Trials (6 papers), Pregnancy and preeclampsia studies (4 papers), Retinal Diseases and Treatments (4 papers), Retinal Imaging and Analysis (4 papers), Obesity, Physical Activity, Diet (4 papers) and Gestational Diabetes Research and Management (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (699 citations), Public Health, Environmental and Occupational Health (2.0k citations) and Pharmacy (284 citations). Mark Simmonds has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Alexis Llewellyn, Nerys Woolacott, Christopher G. Owen, Julian P. T. Higgins, Lesley Stewart, Jayne F. Tierney, Mike Clarke, Gavin Stewart, Richard D Riley and Maroeska M. Rovers. Their work appears in journals such as Health Technology Assessment, Research Synthesis Methods, PharmacoEconomics, PLoS ONE and Systematic Reviews.

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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