S. Lynne Stokes

1.6k total citations
32 papers, 1.1k citations indexed

About

S. Lynne Stokes is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty. According to data from OpenAlex, S. Lynne Stokes has authored 32 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistics and Probability, 7 papers in Management Science and Operations Research and 7 papers in Statistics, Probability and Uncertainty. Recurrent topics in S. Lynne Stokes's work include Advanced Statistical Methods and Models (8 papers), Statistical Methods and Bayesian Inference (7 papers) and Advanced Statistical Process Monitoring (7 papers). S. Lynne Stokes is often cited by papers focused on Advanced Statistical Methods and Models (8 papers), Statistical Methods and Bayesian Inference (7 papers) and Advanced Statistical Process Monitoring (7 papers). S. Lynne Stokes collaborates with scholars based in United States. S. Lynne Stokes's co-authors include Thomas W. Sager, Betsy S. Greenberg, Jing Cao, George T. Duncan, James E. Hines, Michael J. Conroy, James D. Nichols, J. Arthur Gillaspy, Christopher J. Campbell and Bryon Adinoff and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Biometrics.

In The Last Decade

S. Lynne Stokes

29 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Lynne Stokes United States 13 797 505 124 94 82 32 1.1k
Kazuhiro Ohtani Japan 18 578 0.7× 141 0.3× 58 0.5× 61 0.6× 15 0.2× 110 1.1k
Katherine K. Wallman United States 8 427 0.5× 71 0.1× 98 0.8× 101 1.1× 16 0.2× 17 882
Stephen E. Fienberg United States 7 177 0.2× 47 0.1× 49 0.4× 125 1.3× 44 0.5× 8 713
Joseph B. Lang United States 17 505 0.6× 48 0.1× 115 0.9× 162 1.7× 21 0.3× 38 967
Janis E. Johnston United States 14 108 0.1× 93 0.2× 49 0.4× 43 0.5× 45 0.5× 46 412
Jim Albert United States 13 277 0.3× 49 0.1× 76 0.6× 168 1.8× 10 0.1× 52 714
Yves Tillé Switzerland 15 348 0.4× 66 0.1× 59 0.5× 154 1.6× 59 0.7× 71 784
S. H. C. du Toit United States 11 133 0.2× 23 0.0× 91 0.7× 50 0.5× 40 0.5× 13 545
Jeroen Pannekoek Netherlands 10 203 0.3× 18 0.0× 87 0.7× 228 2.4× 118 1.4× 25 772
Sara van Erp Netherlands 7 111 0.1× 63 0.1× 50 0.4× 56 0.6× 10 0.1× 11 412

Countries citing papers authored by S. Lynne Stokes

Since Specialization
Citations

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

Fields of papers citing papers by S. Lynne Stokes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Lynne Stokes. 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 S. Lynne Stokes. The network helps show where S. Lynne Stokes may publish in the future.

Co-authorship network of co-authors of S. Lynne Stokes

This figure shows the co-authorship network connecting the top 25 collaborators of S. Lynne Stokes. A scholar is included among the top collaborators of S. Lynne Stokes 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 S. Lynne Stokes. S. Lynne Stokes 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.
Stokes, S. Lynne, et al.. (2022). Validating matches of electronically reported fishing trips to investigate matching error. Transactions of the American Fisheries Society. 152(1). 114–126. 1 indexed citations
2.
Stokes, S. Lynne, et al.. (2022). Investigating record linkage for combining voluntary catch reports with a probability sample. Fisheries Research. 251. 106301–106301. 4 indexed citations
3.
Duncan, George T., Sallie Keller‐McNulty, & S. Lynne Stokes. (2018). Disclosure Risk vs. Data Utility through the R-U Confidentiality Map in Multivariate Settings. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University).
4.
Duncan, George T., Sallie Keller‐McNulty, & S. Lynne Stokes. (2018). Disclosure Risk vs. Data Utility: The R-U Confidentiality Map. Figshare. 8 indexed citations
5.
Cao, Jing & S. Lynne Stokes. (2007). Bayesian IRT Guessing Models for Partial Guessing Behaviors. Psychometrika. 73(2). 209–230. 50 indexed citations
6.
Wang, Xinlei, Johan Lim, & S. Lynne Stokes. (2006). Forming post-strata via Bayesian treed capture-recapture models. Biometrika. 93(4). 861–876. 1 indexed citations
7.
Falbo, Toni, et al.. (2005). Antecedents and consequences of residential choice and school transfer.. Education Policy Analysis Archives. 13. 29–29. 3 indexed citations
8.
Stokes, S. Lynne. (2003). USING AUXILIARY INFORMATION FOR IMPROVING ESTIMATION IN THE NUMBER OF SPECIES PROBLEM. 1 indexed citations
9.
Anderson, Michael T., Betsy S. Greenberg, & S. Lynne Stokes. (2001). Acceptance Sampling with Rectification When Inspection Errors are Present. Journal of Quality Technology. 33(4). 493–505. 6 indexed citations
10.
Stokes, S. Lynne & Kenneth S. Stephens. (1996). How to Perform Continuous Sampling. Technometrics. 38(1). 82–82. 4 indexed citations
11.
Greenberg, Betsy S. & S. Lynne Stokes. (1995). Repetitive Testing in the Presence of inspection Errors. Technometrics. 37(1). 102–111. 35 indexed citations
12.
Greenberg, Betsy S. & S. Lynne Stokes. (1992). Estimating Nonconformance Rates after Zero-Defect Sampling with Rectification. Technometrics. 34(2). 203–203. 6 indexed citations
13.
Greenberg, Betsy S. & S. Lynne Stokes. (1992). Estimating Nonconformance Rates After Zero-Defect Sampling With Rectification. Technometrics. 34(2). 203–213. 5 indexed citations
14.
Stokes, S. Lynne & Thomas W. Sager. (1988). Characterization of a Ranked-Set Sample with Application to Estimating Distribution Functions. Journal of the American Statistical Association. 83(402). 374–374. 49 indexed citations
15.
Biemer, Paul P. & S. Lynne Stokes. (1985). Optimal Design of Interviewer Variance Experiments in Complex Surveys. Journal of the American Statistical Association. 80(389). 158–166. 17 indexed citations
16.
Biemer, Paul P. & S. Lynne Stokes. (1985). Optimal Design of Interviewer Variance Experiments in Complex Surveys. Journal of the American Statistical Association. 80(389). 158–158. 1 indexed citations
17.
Stokes, S. Lynne. (1984). The Jolly-Seber Method Applied to Age-Stratified Populations. Journal of Wildlife Management. 48(3). 1053–1053. 20 indexed citations
18.
Stokes, S. Lynne. (1980). Inferences on the Correlation Coefficient in Bivariate Normal Populations From Ranked Set Samples. Journal of the American Statistical Association. 75(372). 989–989. 9 indexed citations
19.
Stokes, S. Lynne. (1980). Inferences on the Correlation Coefficient in Bivariate Normal Populations from Ranked Set Samples. Journal of the American Statistical Association. 75(372). 989–995. 54 indexed citations
20.
Stokes, S. Lynne. (1980). Estimation of Variance Using Judgment Ordered Ranked Set Samples. Biometrics. 36(1). 35–35. 162 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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