Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Design of Experiments: Statistical Principles of Research Design and Analysis
2001563 citationsMark J. Anderson, Patrick J. WhitcombTechnometricsprofile →
Countries citing papers authored by Patrick J. Whitcomb
Since
Specialization
Citations
This map shows the geographic impact of Patrick J. Whitcomb'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 Patrick J. Whitcomb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick J. Whitcomb more than expected).
Fields of papers citing papers by Patrick J. Whitcomb
This network shows the impact of papers produced by Patrick J. Whitcomb. 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 Patrick J. Whitcomb. The network helps show where Patrick J. Whitcomb may publish in the future.
Co-authorship network of co-authors of Patrick J. Whitcomb
This figure shows the co-authorship network connecting the top 25 collaborators of Patrick J. Whitcomb.
A scholar is included among the top collaborators of Patrick J. Whitcomb 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 Patrick J. Whitcomb. Patrick J. Whitcomb 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.
Anderson, Mark J., et al.. (2018). Formulation Simplified: Finding the Sweet Spot through Design and Analysis of Experiments with Mixtures. CERN Document Server (European Organization for Nuclear Research).10 indexed citations
2.
Anderson, Mark J., et al.. (2018). Formulation Simplified. Productivity Press eBooks.11 indexed citations
3.
Anderson, Mark J. & Patrick J. Whitcomb. (2016). RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, Second Edition.12 indexed citations
4.
Anderson, Mark J. & Patrick J. Whitcomb. (2016). RSM Simplified. Productivity Press eBooks.102 indexed citations
Anderson, Mark J. & Patrick J. Whitcomb. (2001). Design of Experiments: Statistical Principles of Research Design and Analysis. Technometrics. 43(2). 236–237.563 indexed citations breakdown →
18.
Anderson, Mark J. & Patrick J. Whitcomb. (2000). DOE Simplified: Practical Tools for Effective Experimentation. CERN Document Server (European Organization for Nuclear Research).255 indexed citations
19.
Anderson, Mark J. & Patrick J. Whitcomb. (1996). Optimization of paint formulations made easy with computer-aided design of experiments for mixtures. Journal of Coatings Technology. 68(858). 71–75.10 indexed citations
20.
Anderson, Mark J. & Patrick J. Whitcomb. (1996). Optimize your process-optimization efforts. Chemical engineering progress. 92(12). 51–60.11 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.