Michael Meyners

1.8k total citations · 1 hit paper
47 papers, 1.3k citations indexed

About

Michael Meyners is a scholar working on Food Science, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Michael Meyners has authored 47 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Food Science, 15 papers in Statistics and Probability and 10 papers in Management Science and Operations Research. Recurrent topics in Michael Meyners's work include Sensory Analysis and Statistical Methods (33 papers), Biochemical Analysis and Sensing Techniques (10 papers) and Olfactory and Sensory Function Studies (9 papers). Michael Meyners is often cited by papers focused on Sensory Analysis and Statistical Methods (33 papers), Biochemical Analysis and Sensing Techniques (10 papers) and Olfactory and Sensory Function Studies (9 papers). Michael Meyners collaborates with scholars based in Germany, Norway and Australia. Michael Meyners's co-authors include John C. Castura, B. Thomas Carr, Sara R. Jaeger, Gastón Ares, Anne Hasted, Joachim Kunert, Nicolas Pineau, Letícia Vidal, Duncan Hedderley and El Mostafa Qannari and has published in prestigious journals such as PLoS ONE, Journal of Agricultural and Food Chemistry and Food Research International.

In The Last Decade

Michael Meyners

42 papers receiving 1.2k citations

Hit Papers

Existing and new approaches for the analysis of CATA data 2013 2026 2017 2021 2013 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Meyners Germany 16 1.0k 476 242 214 209 47 1.3k
Ian Wakeling United Kingdom 18 888 0.9× 438 0.9× 146 0.6× 258 1.2× 118 0.6× 29 1.5k
Jian Bi United States 21 847 0.8× 408 0.9× 181 0.7× 170 0.8× 208 1.0× 89 1.3k
John C. Castura Uruguay 22 1.5k 1.5× 898 1.9× 455 1.9× 281 1.3× 396 1.9× 48 1.7k
Jean A. McEwan United Kingdom 17 785 0.8× 386 0.8× 135 0.6× 239 1.1× 180 0.9× 34 975
Michel Visalli France 19 809 0.8× 462 1.0× 319 1.3× 99 0.5× 280 1.3× 60 1.0k
Sylvie Cordelle France 12 723 0.7× 452 0.9× 200 0.8× 176 0.8× 190 0.9× 17 897
Daniel M. Ennis United States 23 1.3k 1.3× 802 1.7× 290 1.2× 183 0.9× 426 2.0× 83 1.8k
Sylvie Chollet France 23 1.5k 1.5× 684 1.4× 332 1.4× 276 1.3× 291 1.4× 51 1.9k
Michael O’Mahony United States 28 1.6k 1.6× 1.1k 2.4× 615 2.5× 246 1.1× 566 2.7× 90 2.3k
Jeannine Delwiche United States 21 726 0.7× 778 1.6× 683 2.8× 147 0.7× 287 1.4× 43 1.6k

Countries citing papers authored by Michael Meyners

Since Specialization
Citations

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

Fields of papers citing papers by Michael Meyners

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Meyners

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Meyners. A scholar is included among the top collaborators of Michael Meyners based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Meyners. Michael Meyners is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Castura, John C., Michael Meyners, Terhi Pohjanheimo, Paula Varela, & Tormod Næs. (2023). An approach for clustering consumers by their top‐box and top‐choice responses. Journal of Sensory Studies. 38(5). 2 indexed citations
2.
Meyners, Michael, et al.. (2020). Validation of motion tracking as tool for observational toothbrushing studies. PLoS ONE. 15(12). e0244678–e0244678. 1 indexed citations
3.
Beaton, Derek & Michael Meyners. (2018). Powerful visualization of product-attribute associations for temporal data. Food Quality and Preference. 79. 103572–103572. 8 indexed citations
4.
Meyners, Michael & John C. Castura. (2018). Did assessors select attributes by chance alone in your TDS study, and how relevant is it to know?. Food Research International. 119. 571–583. 16 indexed citations
5.
Meyners, Michael & John C. Castura. (2017). The analysis of temporal check-all-that-apply (TCATA) data. Food Quality and Preference. 67. 67–76. 36 indexed citations
6.
Meyners, Michael, Sara R. Jaeger, & Gastón Ares. (2015). On the analysis of Rate-All-That-Apply (RATA) data. Food Quality and Preference. 49. 1–10. 139 indexed citations
7.
Meyners, Michael & John C. Castura. (2015). Randomization of CATA attributes: Should attribute lists be allocated to assessors or to samples?. Food Quality and Preference. 48. 210–215. 92 indexed citations
8.
Meyners, Michael, John C. Castura, & Thierry Worch. (2015). Statistical evaluation of panel repeatability in Check-All-That-Apply questions. Food Quality and Preference. 49. 197–204. 14 indexed citations
9.
Meyners, Michael. (2014). Testing for differences between impact of attributes in penalty-lift analysis. Food Quality and Preference. 47. 29–33. 14 indexed citations
10.
Meyners, Michael. (2012). Equivalence tests – A review. Food Quality and Preference. 26(2). 231–245. 77 indexed citations
11.
Meyners, Michael. (2011). Sample Size Determination for Testing the Variance Compound in a One-Way Random Effects Model. Quality Technology & Quantitative Management. 8(2). 101–109. 2 indexed citations
12.
Meyners, Michael & Nicolas Pineau. (2010). Statistical inference for temporal dominance of sensations data using randomization tests. Food Quality and Preference. 21(7). 805–814. 40 indexed citations
13.
Meyners, Michael, et al.. (2009). The cross-modal effect of fragrance in shampoo: Modifying the perceived feel of both product and hair during and after washing. Food Quality and Preference. 20(4). 320–328. 34 indexed citations
14.
Duineveld, C.A.A., et al.. (2006). Retronasal odor dependence on tastants in profiling studies of beverages. Food Quality and Preference. 18(2). 286–295. 15 indexed citations
15.
Meyners, Michael. (2006). Least equivalent allowable differences in equivalence testing. Food Quality and Preference. 18(3). 541–547. 18 indexed citations
16.
King, Bonnie M., et al.. (2006). Sweetener/Sweetness-Induced Changes in Flavor Perception and Flavor Release of Fruity and Green Character in Beverages. Journal of Agricultural and Food Chemistry. 54(7). 2671–2677. 28 indexed citations
17.
Markert, Michael & Michael Meyners. (2004). Correcting the QT Interval for Changes in HR in Pre-clinical Drug Development. Methods of Information in Medicine. 43(5). 445–450. 9 indexed citations
18.
Meyners, Michael. (2001). On the number of perceivers in a triangle test with replications. Econstor (Econstor). 3 indexed citations
19.
Meyners, Michael. (2001). Permutation tests: are there differences in product liking?. Food Quality and Preference. 12(5-7). 345–351. 12 indexed citations
20.
Meyners, Michael, Joachim Kunert, & El Mostafa Qannari. (2000). Comparing generalized procrustes analysis and statis. Food Quality and Preference. 11(1-2). 77–83. 30 indexed citations

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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