Regression methods in biostatistics. Linear, logistic, survival, and repeated measures models.

DOI10.1007/978-1-4614-1353-0zbMath1320.92009OpenAlexW4234686673WikidataQ104282127 ScholiaQ104282127MaRDI QIDQ5894306

Charles E. McCulloch, Eric Vittinghoff, David V. Glidden, Stephen C. Shiboski

Publication date: 21 October 2011

Published in: Statistics for Biology and Health (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4614-1353-0

zbMATH Keywords

regression analysisCox modellogistic models for binary outcomesnegative binomial models

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) General nonlinear regression (62J02) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics (62-01) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to biology (92-01)

Related Items (5)

A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension ⋮ Phase I risk-adjusted control charts for surgical data with ordinal outcomes ⋮ Testing covariates in high-dimensional regression ⋮ A hierarchical model for the joint mortality analysis of pension scheme data with missing covariates ⋮ Confidence intervals for difference between two binomial proportions derived from logistic regression

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