J
John Concato
Researcher at Yale University
Publications - 251
Citations - 30777
John Concato is an academic researcher from Yale University. The author has contributed to research in topics: Population & Prostate cancer. The author has an hindex of 61, co-authored 241 publications receiving 26637 citations. Previous affiliations of John Concato include Boston University & Veterans Health Administration.
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Journal ArticleDOI
A simulation study of the number of events per variable in logistic regression analysis.
Peter Peduzzi,John Concato,John Concato,Elizabeth Kemper,Elizabeth Kemper,Theodore R. Holford,Alvan R. Feinstein,Alvan R. Feinstein +7 more
TL;DR: Findings indicate that low EPV can lead to major problems, and the regression coefficients were biased in both positive and negative directions, and paradoxical associations (significance in the wrong direction) were increased.
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Randomized, controlled trials, observational studies, and the hierarchy of research designs.
TL;DR: The results of well-designed observational studies (with either a cohort or a case-control design) do not systematically overestimate the magnitude of the effects of treatment as compared with those in randomized, controlled trials on the same topic.
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Obstructive sleep apnea as a risk factor for stroke and death.
H. Klar Yaggi,John Concato,Walter N. Kernan,Judith H. Lichtman,Lawrence M. Brass,Vahid Mohsenin +5 more
TL;DR: The obstructive sleep apnea syndrome significantly increases the risk of stroke or death from any cause, and the increase is independent of other risk factors, including hypertension.
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Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates
TL;DR: The analytical effect of the number of events per variable (EPV) in a proportional hazards regression analysis was evaluated using Monte Carlo simulation techniques for data from a randomized trial containing 673 patients and 252 deaths, in which seven predictor variables had an original significance level of p < 0.10.
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The risk of determining risk with multivariable models.
TL;DR: The purpose in the current research was to note the frequency with which multivariable analyses now appear in general medical journals, to identify some common problems and desirable precautions in the analyses, and to determine how well the challenges are being met.