J. S. Williams

406 total citations
13 papers, 283 citations indexed

About

J. S. Williams is a scholar working on Statistics and Probability, Epidemiology and Surgery. According to data from OpenAlex, J. S. Williams has authored 13 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistics and Probability, 2 papers in Epidemiology and 1 paper in Surgery. Recurrent topics in J. S. Williams's work include Statistical Methods and Bayesian Inference (4 papers), Advanced Statistical Methods and Models (4 papers) and Statistical Methods and Inference (4 papers). J. S. Williams is often cited by papers focused on Statistical Methods and Bayesian Inference (4 papers), Advanced Statistical Methods and Models (4 papers) and Statistical Methods and Inference (4 papers). J. S. Williams collaborates with scholars based in United States. J. S. Williams's co-authors include Stephen W. Lagakos, T. M. Sutherland, Thomas R. Bement, Glenn N. Taylor, Charles W. Mays and Alan Julian Izenman and has published in prestigious journals such as Journal of the American Statistical Association, Genetics and Biometrics.

In The Last Decade

J. S. Williams

13 papers receiving 228 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. S. Williams United States 7 140 56 31 26 24 13 283
M. R. Srinivasan India 10 56 0.4× 75 1.3× 7 0.2× 57 2.2× 25 1.0× 60 283
W. F. Scott United Kingdom 9 41 0.3× 6 0.1× 2 0.1× 19 0.7× 17 0.7× 23 246
J. E. Kerrich South Africa 7 79 0.6× 6 0.1× 5 0.2× 27 1.0× 39 1.6× 16 330
Jinadasa Gamage United States 7 102 0.7× 135 2.4× 68 2.2× 27 1.0× 14 0.6× 13 308
Maurice Whittinghill United States 7 61 0.4× 36 0.6× 3 0.1× 10 0.4× 29 1.2× 15 305
Juhee Lee United States 11 144 1.0× 18 0.3× 20 0.6× 29 1.1× 31 1.3× 30 402
Ya‐Mei Chang Taiwan 9 65 0.5× 7 0.1× 45 1.5× 17 0.7× 30 1.3× 19 336
Ondřej Vencálek Czechia 8 39 0.3× 10 0.2× 13 0.4× 8 0.3× 9 0.4× 36 269
Özlem İlk Türkiye 11 33 0.2× 16 0.3× 16 0.5× 4 0.2× 16 0.7× 23 294
John Verzani United States 5 30 0.2× 8 0.1× 5 0.2× 10 0.4× 28 1.2× 10 189

Countries citing papers authored by J. S. Williams

Since Specialization
Citations

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

Fields of papers citing papers by J. S. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. S. Williams

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

All Works

13 of 13 papers shown
1.
Williams, J. S., et al.. (1995). Experimental Noise Path Analysis for Problem Identification in Automobiles. 2460. 442. 6 indexed citations
2.
Izenman, Alan Julian & J. S. Williams. (1989). A Class of Linear Spectral Models and Analyses for the Study of Longitudinal data. Biometrics. 45(3). 831–831. 5 indexed citations
3.
Williams, J. S., et al.. (1978). Models for Censored Survival Analysis: A Cone Class of Variable-Sum Models. Biometrika. 65(1). 181–181. 1 indexed citations
4.
Lagakos, Stephen W. & J. S. Williams. (1978). Models for censored survival analysis: A cone class of variable-sum models. Biometrika. 65(1). 181–189. 34 indexed citations
5.
Williams, J. S.. (1978). Efficient Analysis of Weibull Survival Data from Experiments on Heterogeneous Patient Populations. Biometrics. 34(2). 209–209. 14 indexed citations
6.
Williams, J. S. & Stephen W. Lagakos. (1977). Models for censored survival analysis: Constant-sum and variable-sum models. Biometrika. 64(2). 215–224. 58 indexed citations
7.
Taylor, Glenn N., et al.. (1976). Mammary neoplasia in a closed beagle colony.. PubMed. 36(8). 2740–3. 40 indexed citations
8.
Williams, J. S.. (1970). The Choice and Use of Tests for the Independence of Two Sets of Variates. Biometrics. 26(4). 613–613. 1 indexed citations
9.
Bement, Thomas R. & J. S. Williams. (1969). Variance of Weighted Regression Estimators when Sampling Errors are Independent and Heteroscedastic. Journal of the American Statistical Association. 64(328). 1369–1382. 27 indexed citations
10.
Bement, Thomas R. & J. S. Williams. (1969). Variance of Weighted Regression Estimators when Sampling Errors are Independent and Heteroscedastic. Journal of the American Statistical Association. 64(328). 1369–1369. 5 indexed citations
11.
Williams, J. S.. (1967). The Variance of Weighted Regression Estimators. Journal of the American Statistical Association. 62(320). 1290–1290. 6 indexed citations
12.
Sutherland, T. M., et al.. (1967). PRENATAL AND POSTNATAL MATERNAL INFLUENCE ON GROWTH IN MICE. Genetics. 57(1). 79–94. 66 indexed citations
13.
Williams, J. S.. (1967). The Variance of Weighted Regression Estimators. Journal of the American Statistical Association. 62(320). 1290–1301. 20 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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