Mervyn G. Marasinghe

1.4k total citations · 1 hit paper
36 papers, 1.2k citations indexed

About

Mervyn G. Marasinghe is a scholar working on Statistics and Probability, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Mervyn G. Marasinghe has authored 36 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 5 papers in Artificial Intelligence and 3 papers in Control and Systems Engineering. Recurrent topics in Mervyn G. Marasinghe's work include Statistics Education and Methodologies (5 papers), Statistical Methods and Inference (4 papers) and Advanced Statistical Methods and Models (4 papers). Mervyn G. Marasinghe is often cited by papers focused on Statistics Education and Methodologies (5 papers), Statistical Methods and Inference (4 papers) and Advanced Statistical Methods and Models (4 papers). Mervyn G. Marasinghe collaborates with scholars based in United States, Sri Lanka and Hong Kong. Mervyn G. Marasinghe's co-authors include Rudolf J. Freund, Ramon C. Littell, Dallas E. Johnson, Dianne Cook, William Q. Meeker, Robert J. Boik, Judy M. Vance, William J. Kennedy, Can Chen and Scott Schram and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Biometrics.

In The Last Decade

Mervyn G. Marasinghe

34 papers receiving 1.0k citations

Hit Papers

SAS System for Linear Models 1988 2026 2000 2013 1988 250 500 750
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.

  1. SAS System for Linear Models
    1988 966 citations Mervyn G. Marasinghe et al. Technometrics profile →

Peers

Mervyn G. Marasinghe
Robert O. Kuehl United States
D. J. Saville New Zealand
John Sall United States
F. M. Speed United States
Graham Hepworth Australia
Bo Markussen Denmark
S. G. Carmer United States
Charles E. Gates United States
Christophe Dutang France
J. Richard Alldredge United States
Robert O. Kuehl United States
Mervyn G. Marasinghe
Citations per year, relative to Mervyn G. Marasinghe Mervyn G. Marasinghe (= 1×) peers Robert O. Kuehl

Countries citing papers authored by Mervyn G. Marasinghe

Since Specialization
Citations

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

Fields of papers citing papers by Mervyn G. Marasinghe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mervyn G. Marasinghe. 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 Mervyn G. Marasinghe. The network helps show where Mervyn G. Marasinghe may publish in the future.

Co-authorship network of co-authors of Mervyn G. Marasinghe

This figure shows the co-authorship network connecting the top 25 collaborators of Mervyn G. Marasinghe. A scholar is included among the top collaborators of Mervyn G. Marasinghe 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 Mervyn G. Marasinghe. Mervyn G. Marasinghe 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.
Gunasekara, Chinthika, Manjula Weerasekera, Neluka Fernando, et al.. (2018). Isolation and characterization of Leptospira interrogans from two patients with leptospirosis in Western Province, Sri Lanka. Journal of Medical Microbiology. 67(9). 1249–1252. 12 indexed citations
2.
Marasinghe, Mervyn G. & Kenneth J. Koehler. (2018). Statistical Data Analysis Using SAS. 4 indexed citations
3.
Chen, Can, R. Christopher Williams, Mervyn G. Marasinghe, et al.. (2015). Assessment of Composite Pavement Performance by Survival Analysis. Journal of Transportation Engineering. 141(9). 14 indexed citations
4.
Marasinghe, Mervyn G.. (2015). Jet lag: biology, sleep and coping strategies. 45(1-2). 39–39. 1 indexed citations
5.
Chen, Can, et al.. (2014). Survival Analysis for Composite Pavement Performance in Iowa. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 4 indexed citations
6.
Marasinghe, Mervyn G.. (2011). A Modern Approach to Regression with R by SHEATHER, S. J.. Biometrics. 67(2). 675–677. 3 indexed citations
7.
Marasinghe, Mervyn G. & William J. Kennedy. (2008). SAS for Data Analysis. CERN Document Server (European Organization for Nuclear Research). 7 indexed citations
8.
Marasinghe, Mervyn G., et al.. (2004). Tools for Teaching Regression Concepts Using Dynamic Graphics. Journal of Statistics Education. 12(2). 4 indexed citations
9.
Marasinghe, Mervyn G.. (2002). COMPUTER MODULES FOR TEACHING STATISTICAL CONCEPTS. 2(4). 19–26. 3 indexed citations
10.
Iversen, Philip W. & Mervyn G. Marasinghe. (2001). Dynamic Graphical Tools for Teaching Experimental Design and Analysis Concepts. The American Statistician. 55(4). 345–351. 1 indexed citations
11.
Marasinghe, Mervyn G., et al.. (1996). Using Graphics and Simulation to Teach Statistical Concepts. The American Statistician. 50(4). 342–351. 30 indexed citations
12.
Marasinghe, Mervyn G., et al.. (1989). Analysis of Nonadditive Multiway Classifications. Journal of the American Statistical Association. 84(408). 1059–1059. 2 indexed citations
13.
Boik, Robert J. & Mervyn G. Marasinghe. (1989). Analysis of Nonadditive Multiway Classifications. Journal of the American Statistical Association. 84(408). 1059–1064. 6 indexed citations
14.
Marasinghe, Mervyn G.. (1986). A note on methods for computing Tukey's and Mandel's interaction sums of squares. Communications in Statistics - Simulation and Computation. 15(3). 649–654. 1 indexed citations
15.
Marasinghe, Mervyn G.. (1985). Asymptotic tests and monte carlo studies associated with the multiplicative interaction model. Communication in Statistics- Theory and Methods. 14(9). 2219–2231. 18 indexed citations
16.
Marasinghe, Mervyn G.. (1985). A Multistage Procedure for Detecting Several Outliers in Linear Regression. Technometrics. 27(4). 395–399. 31 indexed citations
17.
Marasinghe, Mervyn G. & Dallas E. Johnson. (1982). A Test of Incomplete Additivity in the Multiplicative Interaction Model. Journal of the American Statistical Association. 77(380). 869–877. 15 indexed citations
18.
Marasinghe, Mervyn G. & Dallas E. Johnson. (1982). A Test of Incomplete Additivity in the Multiplicative Interaction Model. Journal of the American Statistical Association. 77(380). 869–869. 4 indexed citations
19.
Marasinghe, Mervyn G. & Dallas E. Johnson. (1981). Testing Subhypotheses in the Multiplicative Interaction Model. Technometrics. 23(4). 385–393. 14 indexed citations
20.
Marasinghe, Mervyn G. & Dallas E. Johnson. (1981). Testing Subhypotheses in the Multiplicative Interaction Model. Technometrics. 23(4). 385–385. 7 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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