S. R. Searle

20.0k citations
148 papers · 12.3k indexed · 7 hit papers · h-index 35

S. R. Searle

137 papers receiving 11.1k citations

Hit Papers

Linear Models19592026198120031971200019921980198150010001.5k2.0k2.5k

Peers

S. R. Searle
Comparison fields: 5 of 231
  • Statistics and Probability 2.8k
  • Genetics 2.0k
  • Plant Science 1.6k
  • Management Science and Operations Research 1.2k
  • Nature and Landscape Conservation 878
Replace F. N. David with:
F. N. David United Kingdom
Peter McCullagh Australia
William Kruskal United States
David A. Harville United States
Dean W. Wichern United States
Ian T. Jolliffe United Kingdom
William G. Cochran United States
Stephen E. Fienberg United States
Sanford Weisberg United States
George Casella United States
S. R. Searle relative to F. N. David United Kingdom F. N. David's profile →
Citations per field
00.5×1.5×2.5×
F. N. David · 1×
Citations per year

Countries citing papers authored by S. R. Searle

Since Specialization
Citations

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

Fields of papers citing papers by S. R. Searle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. R. Searle

This figure shows the co-authorship network connecting the top 25 collaborators of S. R. Searle. A scholar is included among the top collaborators of S. R. Searle 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. R. Searle. S. R. Searle 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
#WorkIndexed citations
1
Generalized, Linear, and Mixed Modelsbreakdown →
1907
2 53
3 11
4 4
5 12
6
Variance Componentsbreakdown →
1460
7 4
8
Linear models for some-cells-empty data: the cell means formulation, a consultant's best friend
0
9 2
10 4
11 1
12 19
13 1
14
Population Marginal Means in the Linear Model: An Alternative to Least Squares Meansbreakdown →
1372
15 21
16 63
17 28
18
Model Considerations and Variance Component Estimation in Augmented Completely Randomized and Randomized Complete Blocks Designs - Preliminary Version
6
19 4
20 4

About S. R. Searle

S. R. Searle is a scholar working on Statistics and Probability, Computational Theory and Mathematics and Applied Mathematics, having authored 148 papers that have together received 12.3k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (26 papers), Genetic and phenotypic traits in livestock (23 papers) and Statistical Methods and Inference (14 papers). The work is most often cited by research in Statistics and Probability (2.8k citations), Management Science and Operations Research (1.2k citations) and Statistics, Probability and Uncertainty (560 citations). S. R. Searle has collaborated with scholars based in United States, New Zealand and Germany. Frequent co-authors include Charles E. McCulloch, H. V. Henderson, George Casella, F. M. Speed, George A. Milliken, David D. Turner, R. R. Corbeil, Charles Henderson, Oscar Kempthorne and C. M. von Krosigk. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Management Science.

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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