Author
Paul F. Velleman
Other affiliations: National Board of Medical Examiners, Princeton University
Bio: Paul F. Velleman is an academic researcher from Cornell University. The author has contributed to research in topics: Exploratory data analysis & Statistics education. The author has an hindex of 20, co-authored 51 publications receiving 3675 citations. Previous affiliations of Paul F. Velleman include National Board of Medical Examiners & Princeton University.
Papers published on a yearly basis
Papers
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TL;DR: This paper proposes a new general approach, based on the methods of Hadi (1992a,1994) and Hadi and Simonoff (1993) that can be computed quickly — often requiring less than five evaluations of the model being fit to the data, regardless of the sample size.
506 citations
TL;DR: Recently, there has been a renaissance in the use of S.S.Stevens's scale typology for guiding the design of statistical computer packages as discussed by the authors, which ignores important developments in data analysis over the last several decades.
Abstract: The psychophysicist S.S. Stevens developed a measurement scale typology that has dominated social statistics methodology for almost 50 years. During this period, it has generated considerable controversy among statisticians. Recently, there has been a renaissance in the use of Stevens's scale typology for guiding the design of statistical computer packages. The current use of Stevens's terminology fails to deal with the classical criticisms at the time it was proposed and ignores important developments in data analysis over the last several decades.
480 citations
TL;DR: This article attempts to make regression diagnostics more readily available to those who compute regressions with packaged statistics programs, highlighting ambiguities of terminology and relationships among similar methods.
Abstract: Multiple regression diagnostic methods have recently been developed to help data analysts identify failures of data to adhere to the assumptions that customarily accompany regression models. However, the mathematical development of regression diagnostics has not generally led to efficient computing formulas. Conflicting terminology and the use of closely related but subtly different statistics has caused confusion. This article attempts to make regression diagnostics more readily available to those who compute regressions with packaged statistics programs. We review regression diagnostic methodology, highlighting ambiguities of terminology and relationships among similar methods. We present new formulas for efficient computing of regression diagnostics. Finally, we offer specific advice on obtaining regression diagnostics from existing statistics programs, with examples drawn from Minitab and SAS.
339 citations
01 Jan 2016
TL;DR: Carver, R., Everson, M., Gabrosek, J., Horton, N., Lock, R, Mocko, M, Rossman, A., Roswell, G. as mentioned in this paper and Wood, B. (2016). Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016.
Abstract: Scholarly Commons Citation Carver, R., Everson, M., Gabrosek, J., Horton, N., Lock, R., Mocko, M., Rossman, A., Roswell, G. H., Velleman, P., Witmer, J., & Wood, B. (2016). Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016. Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016, (). Retrieved from https://commons.erau.edu/publication/1083
295 citations
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TL;DR: Principal Component Analysis is a multivariate exploratory analysis method useful to separate systematic variation from noise and to define a space of reduced dimensions that preserve noise.
8,660 citations
TL;DR: The increases in the prevalence of obesity previously observed do not appear to be continuing at the same rate over the past 10 years, particularly for women and possibly for men.
Abstract: Results In 2007-2008, the age-adjusted prevalence of obesity was 33.8% (95% confidence interval [CI], 31.6%-36.0%) overall, 32.2% (95% CI, 29.5%-35.0%) among men, and 35.5% (95% CI, 33.2%-37.7%) among women. The corresponding prevalence estimates for overweight and obesity combined (BMI 25) were 68.0% (95% CI, 66.3%-69.8%), 72.3% (95% CI, 70.4%-74.1%), and 64.1% (95% CI, 61.3%66.9%). Obesity prevalence varied by age group and by racial and ethnic group for both men and women. Over the 10-year period, obesity showed no significant trend among women (adjusted odds ratio [AOR] for 2007-2008 vs 1999-2000, 1.12 [95% CI, 0.89-1.32]). For men, there was a significant linear trend (AOR for 2007-2008 vs 1999-2000, 1.32 [95% CI, 1.12-1.58]); however, the 3 most recent data points did not differ significantly from each other.
7,730 citations
TL;DR: The increases in the prevalences of obesity and overweight previously observed continued in 1999-2000, and increases occurred for both men and women in all age groups and for non-Hispanic whites, non- Hispanic blacks, and Mexican Americans.
Abstract: ContextThe prevalence of obesity and overweight increased in the United States
between 1978 and 1991. More recent reports have suggested continued increases
but are based on self-reported data.ObjectiveTo examine trends and prevalences of overweight (body mass index [BMI]
≥25) and obesity (BMI ≥30), using measured height and weight data.Design, Setting, and ParticipantsSurvey of 4115 adult men and women conducted in 1999 and 2000 as part
of the National Health and Nutrition Examination Survey (NHANES), a nationally
representative sample of the US population.Main Outcome MeasureAge-adjusted prevalence of overweight, obesity, and extreme obesity
compared with prior surveys, and sex-, age-, and race/ethnicity–specific
estimates.ResultsThe age-adjusted prevalence of obesity was 30.5% in 1999-2000 compared
with 22.9% in NHANES III (1988-1994; P<.001).
The prevalence of overweight also increased during this period from 55.9%
to 64.5% (P<.001). Extreme obesity (BMI ≥40)
also increased significantly in the population, from 2.9% to 4.7% (P = .002). Although not all changes were statistically significant,
increases occurred for both men and women in all age groups and for non-Hispanic
whites, non-Hispanic blacks, and Mexican Americans. Racial/ethnic groups did
not differ significantly in the prevalence of obesity or overweight for men.
Among women, obesity and overweight prevalences were highest among non-Hispanic
black women. More than half of non-Hispanic black women aged 40 years or older
were obese and more than 80% were overweight.ConclusionsThe increases in the prevalences of obesity and overweight previously
observed continued in 1999-2000. The potential health benefits from reduction
in overweight and obesity are of considerable public health importance.
6,523 citations
01 May 1981
TL;DR: This chapter discusses Detecting Influential Observations and Outliers, a method for assessing Collinearity, and its applications in medicine and science.
Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.
4,948 citations
Book•
17 May 2013
TL;DR: This research presents a novel and scalable approach called “Smartfitting” that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of designing and implementing statistical models for regression models.
Abstract: General Strategies.- Regression Models.- Classification Models.- Other Considerations.- Appendix.- References.- Indices.
3,672 citations