Stephen M. Scariano

679 total citations
35 papers, 520 citations indexed

About

Stephen M. Scariano is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Stephen M. Scariano has authored 35 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics, Probability and Uncertainty, 15 papers in Statistics and Probability and 5 papers in Management Science and Operations Research. Recurrent topics in Stephen M. Scariano's work include Advanced Statistical Process Monitoring (15 papers), Scientific Measurement and Uncertainty Evaluation (9 papers) and Advanced Statistical Methods and Models (6 papers). Stephen M. Scariano is often cited by papers focused on Advanced Statistical Process Monitoring (15 papers), Scientific Measurement and Uncertainty Evaluation (9 papers) and Advanced Statistical Methods and Models (6 papers). Stephen M. Scariano collaborates with scholars based in United States, Algeria and Sri Lanka. Stephen M. Scariano's co-authors include Maria E. Calzada, James M. Davenport, Gemai Chen, Dean M. Young and Di Gao and has published in prestigious journals such as American Journal of Physics, The American Statistician and Journal of Statistical Computation and Simulation.

In The Last Decade

Stephen M. Scariano

31 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen M. Scariano United States 11 320 202 88 77 47 35 520
Jorge Luis Romeu United States 7 76 0.2× 102 0.5× 18 0.2× 32 0.4× 5 0.1× 27 324
Pınar Yıldız Türkiye 7 53 0.2× 11 0.1× 33 0.4× 89 1.2× 7 0.1× 20 340
Teri Reed Rhoads United States 11 63 0.2× 94 0.5× 21 0.2× 6 0.1× 10 0.2× 31 322
Erman Çakıt Türkiye 12 38 0.1× 4 0.0× 13 0.1× 39 0.5× 10 0.2× 45 376
Arthur J. Swersey United States 10 25 0.1× 13 0.1× 8 0.1× 39 0.5× 16 0.3× 22 279
Carl Friddle United States 9 24 0.1× 24 0.1× 27 0.3× 6 0.1× 10 0.2× 36 363
Terry A. Bresnick United States 10 23 0.1× 5 0.0× 45 0.5× 105 1.4× 36 0.8× 17 323
Der‐Fa Chen Taiwan 10 35 0.1× 4 0.0× 67 0.8× 12 0.2× 3 0.1× 38 346
Nopasit Chakpitak Thailand 10 16 0.1× 3 0.0× 45 0.5× 30 0.4× 20 0.4× 83 423
Huining Pei China 7 18 0.1× 4 0.0× 15 0.2× 56 0.7× 11 0.2× 22 277

Countries citing papers authored by Stephen M. Scariano

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Scariano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen M. Scariano. 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 Stephen M. Scariano. The network helps show where Stephen M. Scariano may publish in the future.

Co-authorship network of co-authors of Stephen M. Scariano

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen M. Scariano. A scholar is included among the top collaborators of Stephen M. Scariano 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 Stephen M. Scariano. Stephen M. Scariano 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.
Gao, Di & Stephen M. Scariano. (2021). The benefits of teaching Inverse Regression alongside Least Squares Regression: Graphical and numerical comparisons. 2(1). 16–28.
2.
Scariano, Stephen M., et al.. (2013). Is the home-field advantage in limited overs one-day international cricket only for day matches?. 47(1). 1–13. 5 indexed citations
3.
Calzada, Maria E. & Stephen M. Scariano. (2011). A synthetic control chart for the coefficient of variation. Journal of Statistical Computation and Simulation. 83(5). 853–867. 118 indexed citations
4.
Scariano, Stephen M. & Maria E. Calzada. (2009). The Generalized Synthetic Chart. Sequential Analysis. 28(1). 54–68. 46 indexed citations
5.
Scariano, Stephen M. & Maria E. Calzada. (2007). Statistical Thinking with Trend Charts. Mathematics Teacher Learning and Teaching PK-12. 100(8). 534–541.
6.
Young, Dean M., et al.. (2005). Estimation-Equivalent Covariance Structures for the Least Squares and Minque Estimators of the Linear Model Variance. Communication in Statistics- Theory and Methods. 34(3). 625–629.
7.
Scariano, Stephen M. & Maria E. Calzada. (2004). Three Perspectives on Teaching Least Squares.. Mathematics and computer education. 38(3). 255–264. 1 indexed citations
8.
Scariano, Stephen M., et al.. (2004). Comparing Location Estimators for Exponential Mixtures Under Pitman's Measure of Closeness. Communication in Statistics- Theory and Methods. 33(1). 29–46. 4 indexed citations
9.
Calzada, Maria E. & Stephen M. Scariano. (2004). Average Run Length Computations for the Three-Way Chart. Communications in Statistics - Simulation and Computation. 33(2). 505–524. 1 indexed citations
10.
Calzada, Maria E. & Stephen M. Scariano. (2003). The Robustness of the MaxEWMA Chart to Non-normality. Communications in Statistics - Simulation and Computation. 32(2). 573–590. 7 indexed citations
11.
Calzada, Maria E. & Stephen M. Scariano. (2003). Contrasting Total Least Squares with Ordinary Least Squares Part II: Examples and Comparisons. Mathematics and computer education. 37(2). 159. 2 indexed citations
12.
Scariano, Stephen M., et al.. (2003). Adapting EWMA Control Charts for Batch-Correlated Data. Quality Engineering. 15(4). 545–556. 3 indexed citations
13.
Calzada, Maria E. & Stephen M. Scariano. (1999). What Is Normal, Anyway?. Mathematics Teacher Learning and Teaching PK-12. 92(8). 682–689. 2 indexed citations
14.
Scariano, Stephen M. & Maria E. Calzada. (1994). The Role of the Graphing Calculator in the Basic Skills Mathematics Curriculum. Mathematics and computer education. 28(1). 60–69. 3 indexed citations
15.
Scariano, Stephen M., et al.. (1990). Comparisons of changepoint estimators. Communications in Statistics - Simulation and Computation. 19(2). 619–636. 1 indexed citations
16.
Scariano, Stephen M., et al.. (1988). Nonparametric point estimators for the change-point problem. Communication in Statistics- Theory and Methods. 17(11). 3645–3675. 6 indexed citations
17.
Scariano, Stephen M., et al.. (1988). An algorithm for computing nonparametric estimators of change‐points. Communications in Statistics - Simulation and Computation. 17(4). 1511–1532. 1 indexed citations
18.
Scariano, Stephen M. & James M. Davenport. (1987). The Effects of Violations of Independence Assumptions in the One-Way ANOVA. The American Statistician. 41(2). 123–123. 23 indexed citations
19.
Scariano, Stephen M. & James M. Davenport. (1986). A four-moment approach and other practical solutions to the behrens-f1sher problem. Communication in Statistics- Theory and Methods. 15(5). 1467–1505. 6 indexed citations
20.
Scariano, Stephen M. & James M. Davenport. (1984). Corrected f-tests in the general linear model. Communication in Statistics- Theory and Methods. 13(25). 3155–3172. 4 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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