J. Sedransk

1.4k total citations
68 papers, 961 citations indexed

About

J. Sedransk is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, J. Sedransk has authored 68 papers receiving a total of 961 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 10 papers in Management Science and Operations Research. Recurrent topics in J. Sedransk's work include Statistical Methods and Bayesian Inference (28 papers), Bayesian Methods and Mixture Models (11 papers) and Survey Sampling and Estimation Techniques (11 papers). J. Sedransk is often cited by papers focused on Statistical Methods and Bayesian Inference (28 papers), Bayesian Methods and Mixture Models (11 papers) and Survey Sampling and Estimation Techniques (11 papers). J. Sedransk collaborates with scholars based in United States, Canada and United Kingdom. J. Sedransk's co-authors include Donald Malec, Balgobin Nandram, Carol A. Gotway, Walter Liggett, Kenneth H. Reckhow, Linda J. Young, Don Edwards, Stephen L. Rathbun, Anthony R. Olsen and Felicia LeClere and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

J. Sedransk

64 papers receiving 874 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. Sedransk United States 18 417 139 133 101 92 68 961
V. K. Srivastava India 17 408 1.0× 109 0.8× 159 1.2× 60 0.6× 48 0.5× 121 1.3k
Lucio Barabesi Italy 17 373 0.9× 119 0.9× 77 0.6× 116 1.1× 51 0.6× 91 1.0k
Lukas Stefanski Germany 9 911 2.2× 155 1.1× 194 1.5× 33 0.3× 113 1.2× 27 1.7k
Murali Haran United States 21 325 0.8× 235 1.7× 259 1.9× 99 1.0× 43 0.5× 56 1.5k
Yongyi Min United States 6 382 0.9× 104 0.7× 90 0.7× 24 0.2× 73 0.8× 7 764
T. Goicoa Spain 21 284 0.7× 85 0.6× 345 2.6× 40 0.4× 76 0.8× 61 1.1k
Thiago G. Martins Norway 4 233 0.6× 139 1.0× 187 1.4× 153 1.5× 33 0.4× 9 1.1k
Andreas Brezger Germany 10 611 1.5× 289 2.1× 307 2.3× 27 0.3× 84 0.9× 13 1.3k
Scott H. Holan United States 21 284 0.7× 180 1.3× 284 2.1× 105 1.0× 95 1.0× 94 1.3k
Walter Vandaele Netherlands 6 93 0.2× 49 0.4× 107 0.8× 30 0.3× 70 0.8× 8 895

Countries citing papers authored by J. Sedransk

Since Specialization
Citations

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

Fields of papers citing papers by J. Sedransk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Sedransk

This figure shows the co-authorship network connecting the top 25 collaborators of J. Sedransk. A scholar is included among the top collaborators of J. Sedransk 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. Sedransk. J. Sedransk 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.
Yan, Guofen & J. Sedransk. (2021). Exploring the Use of Subpopulation Membership in Bayesian Hierarchical Model Assessment. Journal of Data Science. 4(4). 413–424.
2.
Nandram, Balgobin, et al.. (2018). Bayesian testing for independence of two categorical variables under two-stage cluster sampling with covariates. Journal of Applied Statistics. 45(13). 2365–2393. 2 indexed citations
3.
Sedransk, J.. (2008). The morris hansen lecture 2007. Assessing the value of Bayesian methods for inference about finite population quantities. Journal of Official Statistics. 24(4). 495–506. 5 indexed citations
4.
Evans, Richard D. & J. Sedransk. (2002). Bayesian methodology for combining the results from different experiments when the specifications for pooling are uncertain: II. Journal of Statistical Planning and Inference. 111(1-2). 95–100. 10 indexed citations
5.
Nandram, Balgobin, J. Sedransk, & Linda Williams Pickle. (2000). Bayesian Analysis and Mapping of Mortality Rates for Chronic Obstructive Pulmonary Disease. Journal of the American Statistical Association. 95(452). 1110–1118. 25 indexed citations
6.
Battaglia, Maurizio, Donald Malec, Bruce D. Spencer, David C. Hoaglin, & J. Sedransk. (1995). Adjusting for Noncoverage of Nontelephone Househods in the National Immunization Survey. 9 indexed citations
7.
Malec, Donald & J. Sedransk. (1993). Bayesian Predictive Inference for Units With Small Sample Sizes. Medical Care. 31(supplement). YS66–YS70. 6 indexed citations
8.
Nandram, Balgobin & J. Sedransk. (1993). Empirical Bayes Estimation for the Finite Population Mean on the Current Occasion. Journal of the American Statistical Association. 88(423). 994–1000. 9 indexed citations
9.
Sedransk, J., et al.. (1992). Secondary Data Analysis when there are Missing Observations. Journal of the American Statistical Association. 87(420). 952–961. 23 indexed citations
10.
Clarke, Graham, et al.. (1989). W. G. Cochran's Impact on Statistics.. Journal of the Royal Statistical Society Series D (The Statistician). 38(2). 148–148. 1 indexed citations
11.
Sedransk, J., et al.. (1986). A Bayesian Procedure for Imputing Missing Values in Sample Surveys. Journal of the American Statistical Association. 81(395). 667–676. 14 indexed citations
12.
Sedransk, J., et al.. (1985). Bayesian Estimation of Finite Population Parameters in Categorical Data Models Incorporating Order Restrictions. Journal of the Royal Statistical Society Series B (Statistical Methodology). 47(3). 519–527. 11 indexed citations
13.
Sedransk, J., et al.. (1983). Lower bounds for confidence coefficients for confidence intervals for finite population quantiles. Communication in Statistics- Theory and Methods. 12(12). 1329–1344. 26 indexed citations
14.
Sedransk, J.. (1977). Sampling Problems in the Estimation of the Money Supply. Journal of the American Statistical Association. 72(359). 516–522. 5 indexed citations
15.
Sedransk, J., et al.. (1974). Comparison of ratio estimators in two-phase sampling. Annals of the Institute of Statistical Mathematics. 26(1). 339–350. 1 indexed citations
16.
Sedransk, J., et al.. (1973). Estimation of domain means using two-phase sampling. Biometrika. 60(2). 387–393. 1 indexed citations
17.
Booth, Gordon D. & J. Sedransk. (1969). Planning Some Two-Factor Comparative Surveys. Journal of the American Statistical Association. 64(326). 560–560. 1 indexed citations
18.
Sedransk, J.. (1967). Designing Some Multi-Factor Analytical Studies. Journal of the American Statistical Association. 62(320). 1121–1139. 7 indexed citations
19.
Sedransk, J., et al.. (1966). A Generalized Technique for Predicting Election Results From Early Returns. Public Opinion Quarterly. 30(3). 416–416. 1 indexed citations
20.
Sedransk, J.. (1966). An application of sequential sampling to analytical surveys. Biometrika. 53(1-2). 85–97.

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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