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  xmlns:dcterms="http://purl.org/dc/terms/"><dc:Title>Modeling count data /  Joseph M. Hilbe.</dc:Title>
<dc:Creator>Hilbe, Joseph M.</dc:Creator>
<dc:Subject>Multivariate analysis.</dc:Subject>
<dc:Subject>Statistics.</dc:Subject>
<dc:Subject>Linear models (Statistics)</dc:Subject>
<dc:Subject>QA278 .H56 2014</dc:Subject>
<dc:Subject>519.535 HIM</dc:Subject>
<dc:Description>Includes index.</dc:Description>
<dc:Description>Bibliography: p. 269-275.</dc:Description>
<dc:Description>"This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of linear regression and works up to an analysis of the Poisson and negative binomial models, and to the problem of overdispersion. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in public health, ecology, econometrics, transportation, and other related fields"-- Provided by publisher.</dc:Description>
<dc:Publisher>Cambridge :  Cambridge University Press,</dc:Publisher>
<dc:Date>2014 (2017 printing).</dc:Date>
<dc:Date>2014 (2017 printing).</dc:Date>
<dc:Date>2014</dc:Date>
<dc:Type>Text</dc:Type>
<dc:Format>xv, 283 p. :</dc:Format>
<dc:Language>eng</dc:Language>

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