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Brian Caffo

Researcher at Johns Hopkins University

Publications -  300
Citations -  14180

Brian Caffo is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Medicine & Markov chain Monte Carlo. The author has an hindex of 55, co-authored 270 publications receiving 12207 citations. Previous affiliations of Brian Caffo include National Institutes of Health & University of Texas Health Science Center at Houston.

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Perioperative mortality and long-term survival following live kidney donation.

TL;DR: Among a cohort of live kidney donors compared with a healthy matched cohort, the mortality rate was not significantly increased after a median of 6.3 years, and long-term risk of death was no higher for live donors than for age- and comorbidity-matched NHANES III participants for all patients and also stratified by age, sex, and race.

Teacher's Corner Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures

Alan Agresti, +1 more
TL;DR: In this article, simple adjustments of these confidence intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples, and one can bypass awkward sample size guidelines and use the same formulas with small and large samples.
Journal ArticleDOI

Decreased connectivity and cerebellar activity in autism during motor task performance

TL;DR: The between-group dissociation of cerebral and cerebellar motor activation represents the first neuroimaging data of motor dysfunction in children with autism, providing insight into potentially abnormal circuits impacting development.
Journal ArticleDOI

Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures

TL;DR: This paper showed that simple adjustments of the standard confidence intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples, and used the same formulas with small and large samples in teaching with these adjusted intervals.