Statistical Methods for Assessing Differential Vaccine Protection Against Human Immunodeficiency Virus Types

DOI10.2307/2533835zbMath1058.62609OpenAlexW2040345478WikidataQ45753683 ScholiaQ45753683MaRDI QIDQ4666022

Mark A. Ashby, Peter B. Gilbert, Steven G. Self

Publication date: 11 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2533835

zbMATH Keywords

human immunodeficiency virusstereotype modelmultinomial logistic regression modelHIV vaccine efficacy trialcumulative logit modelgeneralized logistic regression modelsieve analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (12)

Goodness-of-fit tests for parametric models based on biased samples ⋮ A unified evaluation of differential vaccine efficacy ⋮ Density estimation under a two-sample semiparametric model ⋮ Some statistical issues in the design of HIV-1 vaccine and treatment trials ⋮ Advances in medical statistics arising from the AIDS epidemic ⋮ Leaky vaccines protect highly exposed recipients at a lower rate: implications for vaccine efficacy estimation and sieve analysis ⋮ Analysis of two-sample truncated data using generalized logistic models ⋮ Genome Scanning Tests for Comparing Amino Acid Sequences Between Groups ⋮ On minimum Hellinger distance estimation ⋮ Analysis of two-sample censored data using a semiparametric mixture model ⋮ Large sample theory of maximum likelihood estimates in semiparametric biased sampling models. ⋮ Functional inference in semiparametric models using the piggyback bootstrap

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