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Ingram Olkin
Researcher at Stanford University
Publications - 288
Citations - 79100
Ingram Olkin is an academic researcher from Stanford University. The author has contributed to research in topics: Multivariate statistics & Multivariate normal distribution. The author has an hindex of 79, co-authored 288 publications receiving 74131 citations. Previous affiliations of Ingram Olkin include University of British Columbia & Michigan State University.
Papers
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Incomplete data in sample surveys. Vol. 1: report and case studies
TL;DR: The first volume includes the report of the panel and 10 case studies concerning incomplete data as discussed by the authors, which includes sections on problems of incomplete data measuring and reporting non-response, case studies and a review of relevant theory.
Journal Article
Are Organic Foods Safer or Healthier Than Conventional Alternatives
Crystal Smith-Spangler,Margaret L. Brandeau,Grace E. Hunter,J. Clay Bavinger,Maren Pearson,Paul J. Eschbach,Vandana Sundaram,Hau Liu,Patricia Schirmer,Christopher D Stave,Ingram Olkin,Dena M. Bravata +11 more
TL;DR: In this article, a systematic review compared the evidence from 237 studies on the health, nutritional, and safety characteristics of organic and conventional foods and found that the published literature lacks sufficient evidence to compare them.
Journal ArticleDOI
Integral expressions for tail probabilities of the multinomial and negative multinomial distributions
Ingram Olkin,Milton Sobel +1 more
Journal ArticleDOI
Meta-analysis of effect sizes reported at multiple time points: a multivariate approach.
Thomas A Trikalinos,Ingram Olkin +1 more
TL;DR: A meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects, which is an attractive alternative or complement to performing separate meta-analyses.
Book ChapterDOI
Entropy of the Sum of Independent Bernoulli Random Variables and of the Multinomial Distribution
L.A. Shepp,Ingram Olkin +1 more
TL;DR: For sums of independent Bernoulli random variables and for the multinomial distribution, it was shown that the entropy h gives a measure of the degree of uniformness of the distribution π.