Samuel T. Mayo

1.0k total citations · 1 hit paper
20 papers, 795 citations indexed

About

Samuel T. Mayo is a scholar working on Information Systems, Information Systems and Management and Artificial Intelligence. According to data from OpenAlex, Samuel T. Mayo has authored 20 papers receiving a total of 795 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Information Systems, 2 papers in Information Systems and Management and 2 papers in Artificial Intelligence. Recurrent topics in Samuel T. Mayo's work include Educational Assessment and Improvement (2 papers), Cognitive Abilities and Testing (2 papers) and Educational Technology and Assessment (2 papers). Samuel T. Mayo is often cited by papers focused on Educational Assessment and Improvement (2 papers), Cognitive Abilities and Testing (2 papers) and Educational Technology and Assessment (2 papers). Samuel T. Mayo collaborates with scholars based in United States. Samuel T. Mayo's co-authors include Albert K. Kurtz, Julian C. Stanley and Ardie Lubin and has published in prestigious journals such as Psychological Bulletin, Journal of the American Statistical Association and Review of Educational Research.

In The Last Decade

Samuel T. Mayo

17 papers receiving 720 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Statistical Methods in Education and Psychology.

1980 434 citations Albert K. Kurtz, Samuel T. Mayo et al. Journal of the American Statistical Association profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Samuel T. Mayo United States	6	200	156	108	91	80	20	795
Albert K. Kurtz United States	4	165 0.8×	149 1.0×	108 1.0×	91 1.0×	78 1.0×	11	739
Leslie D. McLean Canada	5	179 0.9×	136 0.9×	81 0.8×	88 1.0×	92 1.1×	16	693
William M. Stallings United States	10	182 0.9×	103 0.7×	84 0.8×	48 0.5×	82 1.0×	44	605
Helen M. Walker	5	94 0.5×	97 0.6×	90 0.8×	78 0.9×	69 0.9×	6	758
Joseph Lev United States	5	96 0.5×	99 0.6×	95 0.9×	76 0.8×	71 0.9×	8	785
Alan L. Sockloff United States	9	202 1.0×	91 0.6×	173 1.6×	143 1.6×	152 1.9×	13	1.1k
Alan E. Hendrickson United Kingdom	5	94 0.5×	95 0.6×	143 1.3×	146 1.6×	206 2.6×	7	958
John P. Poggio United States	13	239 1.2×	282 1.8×	84 0.8×	67 0.7×	81 1.0×	46	722
Abraham S. Luchins United States	15	80 0.4×	138 0.9×	206 1.9×	140 1.5×	210 2.6×	93	1.0k
Robert M. Thorndike United States	16	187 0.9×	116 0.7×	160 1.5×	139 1.5×	284 3.5×	35	1.2k

Countries citing papers authored by Samuel T. Mayo

Since Specialization

Citations

This map shows the geographic impact of Samuel T. Mayo'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 Samuel T. Mayo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel T. Mayo more than expected).

Fields of papers citing papers by Samuel T. Mayo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Samuel T. Mayo. 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 Samuel T. Mayo. The network helps show where Samuel T. Mayo may publish in the future.

Co-authorship network of co-authors of Samuel T. Mayo

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel T. Mayo. A scholar is included among the top collaborators of Samuel T. Mayo 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 Samuel T. Mayo. Samuel T. Mayo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Mayo, Samuel T.. (1980). Interpreting test performance. Bibliothèque et Archives nationales du Québec (Québec government). 2 indexed citations

Kurtz, Albert K., et al.. (1980). Statistical Methods in Education and Psychology.. Journal of the American Statistical Association. 75(371). 760–760. 434 indexed citations breakdown →

Kurtz, Albert K. & Samuel T. Mayo. (1979). Instructor’s Manual for Statistical Methods in Education and Psychology. CERN Document Server (European Organization for Nuclear Research).

Kurtz, Albert K. & Samuel T. Mayo. (1979). Statistical Methods in Education and Psychology. CERN Document Server (European Organization for Nuclear Research). 286 indexed citations

Kurtz, Albert K. & Samuel T. Mayo. (1978). Workbook for Statistical Methods in Education and Psychology. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations

Mayo, Samuel T.. (1970). Trends in the Teaching of the First Course in Measurement.. 2 indexed citations

Mayo, Samuel T.. (1970). Measurement in Education: Mastery Learning and Mastery Testing..

Mayo, Samuel T.. (1968). The Methodology and Technology of Educational and Psychological Testing. Review of Educational Research. 38(1). 92–92. 2 indexed citations

Mayo, Samuel T., et al.. (1968). Book Reviews : Desmond L. Cook. The Impact of the Hawthorne Effect in Experimental Designs in Educational Research. U.S. Department of Health, Education, and Welfare, Office of Education, Project No. 1757. Columbus, Ohio: Ohio State University, 1967. Pp. ii + 160. Educational and Psychological Measurement. 28(4). 1255–1259. 1 indexed citations

10.

Mayo, Samuel T.. (1968). Chapter XI: The Methodology and Technology of Educational and Psychological Testing. Review of Educational Research. 38(1). 92–101. 2 indexed citations

11.

Mayo, Samuel T.. (1967). Pre-Service Preparation of Teachers in Educational Measurement. Final Report.. 3 indexed citations

12.

Mayo, Samuel T., et al.. (1966). Measurement and Evaluation in Education, Psychology, and Guidance. American Educational Research Journal. 3(1). 76–76. 30 indexed citations

13.

Mayo, Samuel T.. (1965). Statistical Trends Relevant to Measurement. Review of Educational Research. 35(1). 82–82. 2 indexed citations

14.

Mayo, Samuel T.. (1965). Chapter VII: Statistical Trends Relevant to Measurement. Review of Educational Research. 35(1). 82–91. 1 indexed citations

15.

Mayo, Samuel T.. (1964). WHAT EXPERTS THINK TEACHERS OUGHT TO KNOW ABOUT EDUCATIONAL MEASUREMENT¹. Journal of Educational Measurement. 1(1). 79–86. 14 indexed citations

16.

Stanley, Julian C., et al.. (1961). Interactions in Psychometrics and Experimentation. Educational and Psychological Measurement. 21(4). 791–791. 1 indexed citations

17.

Mayo, Samuel T.. (1961). Interactions Among Categorical Variables. Educational and Psychological Measurement. 21(4). 839–858. 5 indexed citations

18.

Mayo, Samuel T.. (1959). Toward strengthening the contingency table as a statistical method.. Psychological Bulletin. 56(6). 461–470. 5 indexed citations

19.

Mayo, Samuel T.. (1959). Testing and the Use of Test Results. Review of Educational Research. 29(1). 5–5. 1 indexed citations

20.

Mayo, Samuel T.. (1957). Recent Techniques for Analyzing Association in Contingency Tables as Applied to an Analytical Follow-Up Survey of Education Graduates. The Journal of Experimental Education. 25(3). 203–232. 3 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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