David J. Sheskin
David J. Sheskin publishes mostly in Statistics and Probability, Management Science and Operations Research and Food Science, on topics such as Advanced Statistical Methods and Models, Psychometric Methodologies and Testing and Sensory Analysis and Statistical Methods.
- World rank
- #2,919,431 of 7,710,434 ranked researchers
- Rank in United States
- #841,793 of 1,627,098
- Works
- 65
- Citations
- 4.1k
- Citations per work
- 63.7
What does David J. Sheskin research?
David J. Sheskin's work is mostly in Mathematics (36%), Decision Sciences (20%), Agricultural and Biological Sciences (7%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences2741.4%
- Mathematics2436.2%
- Computer Science35.2%
- Everything else1929.2%
- Social Sciences1522.5%
- Decision Sciences1319.9%
- Psychology22.6%
- Life Sciences46.9%
- 1Statistics and Probability36% of their works
- 2Management Science and Operations Research15% of their works
- 3Food Science7% of their works
- 4Artificial Intelligence5% of their works
- 5Statistics, Probability and Uncertainty5% of their works
- 6Applied Psychology3% of their works
Research topics
- Advanced Statistical Methods and Models
- Psychometric Methodologies and Testing
- Sensory Analysis and Statistical Methods
- Statistical Methods and Inference
- Statistical Methods in Clinical Trials
- Statistical Methods and Applications
- Meta-analysis and systematic reviews
- Advanced Statistical Modeling Techniques
Which keywords describe David J. Sheskin's research?
The keywords of their largest research topics: Principal Component Analysis, Regression Analysis, Multicollinearity, Outlier Detection, Measurement Invariance, Multivariate Analysis, Structural Equation Modeling and Bayesian Methods.
- Johnson Noise
- Statistical Modeling
- PRISMA Statement
- Machine Learning
- Adaptive Designs
- Consumer Perception
- Bayesian Methods
- Multivariate Analysis
- Outlier Detection
- Regression Analysis
- Principal Component Analysis
- Multicollinearity
- Measurement Invariance
- Structural Equation Modeling
- Model Selection
- Sensory Analysis
- False Discovery Rate
- Meta-Analysis
- Regularization
- Variable Selection
- Secure Communication
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 21 words, with their numbers
- Principal Component Analysis342 topics
- Regression Analysis342 topics
- Multicollinearity301 topic
- Outlier Detection301 topic
- Measurement Invariance111 topic
- Multivariate Analysis112 topics
- Structural Equation Modeling111 topic
- Bayesian Methods82 topics
- Model Selection82 topics
- Consumer Perception71 topic
- Sensory Analysis71 topic
- Adaptive Designs41 topic
- False Discovery Rate41 topic
- Machine Learning41 topic
- Meta-Analysis41 topic
- PRISMA Statement41 topic
- Regularization41 topic
- Statistical Modeling41 topic
- Variable Selection41 topic
- Johnson Noise31 topic
- Secure Communication31 topic
Where does David J. Sheskin work?
David J. Sheskin's main affiliation in the publication record is Western Connecticut State University, United States.
How many publications and citations does David J. Sheskin have?
OpenAlex counts 65 works and 4,141 citations for David J. Sheskin, an h-index of 10, ranking #2,919,431 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
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