Walter W. Stroup

8.9k total citations · 4 hit papers
105 papers, 7.3k citations indexed

About

Walter W. Stroup is a scholar working on Plant Science, Agronomy and Crop Science and Statistics and Probability. According to data from OpenAlex, Walter W. Stroup has authored 105 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Plant Science, 14 papers in Agronomy and Crop Science and 14 papers in Statistics and Probability. Recurrent topics in Walter W. Stroup's work include Optimal Experimental Design Methods (13 papers), Genetics and Plant Breeding (10 papers) and Turfgrass Adaptation and Management (8 papers). Walter W. Stroup is often cited by papers focused on Optimal Experimental Design Methods (13 papers), Genetics and Plant Breeding (10 papers) and Turfgrass Adaptation and Management (8 papers). Walter W. Stroup collaborates with scholars based in United States, China and Czechia. Walter W. Stroup's co-authors include Ramon C. Littell, George A. Milliken, Russell D. Wolfinger, Oliver Schabenberger, Steven J. Knapp, W. M. Ross, Rudolf J. Freund, Robert A. McLean, William L. Sanders and Drew J. Lyon and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Technometrics.

In The Last Decade

Walter W. Stroup

101 papers receiving 6.8k citations

Hit Papers

SAS for mixed models 1985 2026 1998 2012 2006 1985 2002 2016 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Walter W. Stroup United States 31 2.4k 1.2k 1.1k 961 758 105 7.3k
George A. Milliken United States 38 1.9k 0.8× 930 0.8× 851 0.8× 1.7k 1.7× 1.3k 1.7× 187 10.4k
Mark E. Payton United States 55 3.0k 1.2× 1.6k 1.3× 807 0.7× 1.4k 1.4× 406 0.5× 448 12.4k
R. W. Payne United Kingdom 22 2.4k 1.0× 743 0.6× 457 0.4× 751 0.8× 478 0.6× 69 6.1k
Arnold M. Saxton United States 49 3.0k 1.3× 1.9k 1.5× 1.3k 1.2× 494 0.5× 456 0.6× 296 9.0k
Oliver Schabenberger United States 24 2.6k 1.1× 565 0.5× 443 0.4× 898 0.9× 1.2k 1.6× 40 7.1k
Russell D. Wolfinger United States 39 1.7k 0.7× 559 0.5× 1.4k 1.3× 953 1.0× 751 1.0× 89 9.5k
François Husson France 24 1.9k 0.8× 369 0.3× 879 0.8× 1.6k 1.6× 773 1.0× 70 10.3k
B. R. Cullis Australia 49 6.3k 2.6× 2.0k 1.7× 3.9k 3.6× 642 0.7× 954 1.3× 214 10.2k
Sébastien Lê France 19 1.7k 0.7× 290 0.2× 716 0.7× 1.4k 1.4× 652 0.9× 50 8.6k
Sandy M Thomas United Kingdom 10 3.2k 1.3× 829 0.7× 455 0.4× 1.7k 1.7× 205 0.3× 33 9.1k

Countries citing papers authored by Walter W. Stroup

Since Specialization
Citations

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

Fields of papers citing papers by Walter W. Stroup

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Walter W. Stroup. 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 Walter W. Stroup. The network helps show where Walter W. Stroup may publish in the future.

Co-authorship network of co-authors of Walter W. Stroup

This figure shows the co-authorship network connecting the top 25 collaborators of Walter W. Stroup. A scholar is included among the top collaborators of Walter W. Stroup 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 Walter W. Stroup. Walter W. Stroup 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.
Schwenke, James R., et al.. (2023). Estimating Shelf Life Through Tolerance Intervals Extended to Nonlinear Response Trends. AAPS PharmSciTech. 24(4). 80–80. 1 indexed citations
2.
Schwenke, James R., et al.. (2021). A Practical Discussion on Estimating Shelf Life Through Tolerance Intervals. AAPS PharmSciTech. 22(8). 273–273. 2 indexed citations
3.
Schwenke, James R., et al.. (2020). Estimating Shelf Life Through Tolerance Intervals. AAPS PharmSciTech. 21(8). 290–290. 4 indexed citations
4.
Paparozzi, Ellen T., et al.. (2016). Cytokinin Dynamics during the Response to Nitrogen in Two Contrasting Plectranthus Genotypes. Journal of the American Society for Horticultural Science. 141(3). 264–274. 2 indexed citations
5.
Kramer, Matthew, Ellen T. Paparozzi, & Walter W. Stroup. (2016). Statistics in a Horticultural Journal: Problems and Solutions. Journal of the American Society for Horticultural Science. 141(5). 400–406. 12 indexed citations
6.
Kramer, Matthew, Ellen T. Paparozzi, & Walter W. Stroup. (2016). Statistics in a Horticultural Journal: Problems and Solutions. HortScience. 51(9). 1073–1078. 1 indexed citations
7.
Stroup, Walter W.. (2016). Generalized Linear Mixed Models. 292 indexed citations breakdown →
8.
Xu, Lan, R. N. Gates, Arvid Boe, et al.. (2015). Establishment and Persistence of Yellow‐Flowered Alfalfa No‐Till Interseeded into Crested Wheatgrass Stands. Agronomy Journal. 108(1). 141–150. 8 indexed citations
9.
Quinlan, Michelle, Walter W. Stroup, David Christopher, & James R. Schwenke. (2013). On the Distribution of Batch Shelf Lives. Journal of Biopharmaceutical Statistics. 23(4). 897–920. 5 indexed citations
10.
Gbur, Edward E., Walter W. Stroup, Kevin S. McCarter, et al.. (2012). Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences. Civil War Book Review. 266 indexed citations
11.
Fang, Hua, Kimberly Andrews Espy, Maria L. Rizzo, et al.. (2009). PATTERN RECOGNITION OF LONGITUDINAL TRIAL DATA WITH NONIGNORABLE MISSINGNESS: AN EMPIRICAL CASE STUDY. International Journal of Information Technology & Decision Making. 8(3). 491–513. 21 indexed citations
12.
Espy, Kimberly Andrews, Rebecca Bull, Jessica Martin, & Walter W. Stroup. (2006). Measuring the development of executive control with the shape school.. Psychological Assessment. 18(4). 373–381. 96 indexed citations
13.
Bjerke, Frøydis, Are H. Aastveit, Walter W. Stroup, Bente Kirkhus, & Tormod Næs. (2004). Design and Analysis of Storing Experiments: A Case Study. Quality Engineering. 16(4). 591–611. 4 indexed citations
14.
Stroup, Walter W., et al.. (1998). Statistical Design and Analysis of Producer/Consumer Evaluations to Assess Plant Quality. HortScience. 33(2). 197–202. 1 indexed citations
15.
Paparozzi, Ellen T., et al.. (1997). Nitrogen and Sulfur Effects on the Production and Postharvest Longevity of Pot Chrysanthemums. HortScience. 32(3). 517B–517. 1 indexed citations
16.
Ziegel, Eric R., Ramon C. Littell, George A. Milliken, Walter W. Stroup, & Russ Wolfinger. (1997). SAS® System for Mixed Models. Technometrics. 39(3). 344–344. 73 indexed citations
17.
Stroup, Walter W., et al.. (1991). Nearest Neighbor Adjusted Best Linear Unbiased Prediction. The American Statistician. 45(3). 194–200. 45 indexed citations
18.
McLean, Robert A., William L. Sanders, & Walter W. Stroup. (1991). A Unified Approach to Mixed Linear Models. The American Statistician. 45(1). 54–64. 435 indexed citations
19.
Paparozzi, Ellen T., et al.. (1991). Nitrogen sulfur interaction in poinsettia1. Journal of Plant Nutrition. 14(9). 939–952. 4 indexed citations
20.
Stroup, Walter W., et al.. (1990). Biomass partitioning and root development in annual Medicago spp.. 120(4). 407–416. 3 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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