Stan Lipovetsky

4.3k total citations
194 papers, 3.0k citations indexed

About

Stan Lipovetsky is a scholar working on Statistics and Probability, Management Science and Operations Research and Marketing. According to data from OpenAlex, Stan Lipovetsky has authored 194 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Statistics and Probability, 47 papers in Management Science and Operations Research and 24 papers in Marketing. Recurrent topics in Stan Lipovetsky's work include Advanced Statistical Methods and Models (67 papers), Multi-Criteria Decision Making (26 papers) and Consumer Market Behavior and Pricing (23 papers). Stan Lipovetsky is often cited by papers focused on Advanced Statistical Methods and Models (67 papers), Multi-Criteria Decision Making (26 papers) and Consumer Market Behavior and Pricing (23 papers). Stan Lipovetsky collaborates with scholars based in United States, Israel and Russia. Stan Lipovetsky's co-authors include Michael Conklin, Asher Tishler, W. Michael Conklin, Aaron J. Shenhar, Dov Dvir, В. С. Сенашенко, Jacek Koronacki, В.В. Балашов, Freerk A. Lootsma and Niv Ahituv and has published in prestigious journals such as SHILAP Revista de lepidopterología, Technometrics and European Journal of Operational Research.

In The Last Decade

Stan Lipovetsky

154 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stan Lipovetsky United States 24 1.0k 718 435 310 257 194 3.0k
David J. Bartholomew United Kingdom 27 1.0k 1.0× 1.1k 1.5× 751 1.7× 639 2.1× 138 0.5× 83 5.5k
John Rice Australia 40 495 0.5× 1.3k 1.8× 541 1.2× 612 2.0× 678 2.6× 176 6.2k
Hossein Hassani United Kingdom 38 1.1k 1.1× 210 0.3× 763 1.8× 759 2.4× 132 0.5× 182 5.1k
Hrishikesh D. Vinod United States 27 346 0.3× 661 0.9× 352 0.8× 905 2.9× 157 0.6× 144 3.1k
Peter Hackl Austria 19 506 0.5× 422 0.6× 124 0.3× 212 0.7× 223 0.9× 50 2.2k
Patrick L. Brockett United States 31 1.3k 1.3× 435 0.6× 386 0.9× 1.7k 5.4× 208 0.8× 159 4.1k
Youngjo Lee South Korea 29 383 0.4× 1.3k 1.8× 383 0.9× 419 1.4× 120 0.5× 192 3.6k
S. Kotz United States 23 616 0.6× 1.7k 2.4× 644 1.5× 405 1.3× 78 0.3× 70 4.0k
Antony Unwin Germany 28 664 0.7× 279 0.4× 526 1.2× 285 0.9× 194 0.8× 109 4.3k
Christine M. Anderson‐Cook United States 28 1.5k 1.5× 908 1.3× 367 0.8× 675 2.2× 75 0.3× 239 5.9k

Countries citing papers authored by Stan Lipovetsky

Since Specialization
Citations

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

Fields of papers citing papers by Stan Lipovetsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stan Lipovetsky

This figure shows the co-authorship network connecting the top 25 collaborators of Stan Lipovetsky. A scholar is included among the top collaborators of Stan Lipovetsky 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 Stan Lipovetsky. Stan Lipovetsky 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.
Lipovetsky, Stan & Michael Conklin. (2021). Bayesian Sensitivity-Specificity and ROC Analysis for Finding Key Drivers. Human Biology. 19(1). 2–15. 3 indexed citations
2.
Lipovetsky, Stan. (2020). Regression Modeling and Prediction by Individual Observations versus Frequency. Human Biology. 18(1). 2–19. 4 indexed citations
3.
Lipovetsky, Stan, et al.. (2020). Analytical Closed-Form Solution for General Factor with Many Variables. Human Biology. 18(1). 2–23. 1 indexed citations
4.
Lipovetsky, Stan. (2018). Regressions regularized by correlations. Journal of Modern Applied Statistical Methods. 17(1). 3 indexed citations
5.
Lipovetsky, Stan & Michael Conklin. (2018). Decreasing Respondent Heterogeneity by Likert Scales Adjustment via Multipoles. Stats. 1(1). 169–175. 8 indexed citations
6.
Lipovetsky, Stan. (2017). Factor analysis by limited scales: which factors to analyze?. Journal of Modern Applied Statistical Methods. 16(1). 233–245. 13 indexed citations
7.
Lipovetsky, Stan. (2017). Prediction of Percent Change in Linear Regression by Correlated Variables. Journal of Modern Applied Statistical Methods. 16(2). 347–358. 5 indexed citations
8.
Lipovetsky, Stan. (2016). Generalized Singular Value Decomposition with Additive Components. Journal of Modern Applied Statistical Methods. 15(1). 584–599. 2 indexed citations
9.
Lipovetsky, Stan, et al.. (2015). Modeling Probability of Causal and Random Impacts. Journal of Modern Applied Statistical Methods. 14(1). 180–195. 2 indexed citations
10.
Lipovetsky, Stan. (2013). Priorities in Thurstone Scaling and Steady-State Probabilities in Markov Stochastic Modeling. Journal of Modern Applied Statistical Methods. 12(1). 65–77. 2 indexed citations
11.
Lipovetsky, Stan. (2013). How Good is Best? Multivariate Case of Ehrenberg-Weisberg Analysis of Residual Errors in Competing Regressions. Journal of Modern Applied Statistical Methods. 12(2). 242–255. 12 indexed citations
12.
Lipovetsky, Stan. (2012). Regression Split by Levels of the Dependent Variable. Journal of Modern Applied Statistical Methods. 11(2). 319–324. 4 indexed citations
13.
Lipovetsky, Stan. (2010). Nonlinear Parameterization in Bi-Criteria Sample Balancing. Journal of Modern Applied Statistical Methods. 9(1). 198–208. 2 indexed citations
14.
Lipovetsky, Stan. (2009). Multiple Regression in Pair Correlation Solution. Journal of Modern Applied Statistical Methods. 8(1). 122–131. 2 indexed citations
15.
Lipovetsky, Stan. (2008). Pareto 80/20 law: derivation via random partitioning. International Journal of Mathematical Education in Science and Technology. 40(2). 271–277. 40 indexed citations
16.
Lipovetsky, Stan. (2007). Optimal Lp-Metric for Minimizing Powered Deviations in Regression. Journal of Modern Applied Statistical Methods. 6(1). 219–227. 9 indexed citations
17.
Lipovetsky, Stan. (2006). Entropy Criterion In Logistic Regression And Shapley Value Of Predictors. Journal of Modern Applied Statistical Methods. 5(1). 95–106. 24 indexed citations
18.
Lipovetsky, Stan & Michael Conklin. (2005). Regression By Data Segments Via Discriminant Analysis. Journal of Modern Applied Statistical Methods. 4(1). 63–74. 13 indexed citations
19.
Lipovetsky, Stan & Michael Conklin. (2005). Incremental net effects in multiple regression. International Journal of Mathematical Education in Science and Technology. 36(4). 361–373. 10 indexed citations
20.
Lipovetsky, Stan & W. Michael Conklin. (2004). Enhance-synergism and suppression effects in multiple regression. International Journal of Mathematical Education in Science and Technology. 35(3). 391–402. 14 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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