Regression & linear modeling : best practices and modern methods / Jason W. Osborne.

Format:

Book

Author/Creator:

Osborne, Jason W., author.

Series:

Sage research methods.

Subjects (All):

Regression analysis.

Linear models (Statistics).

Physical Description:

1 online resource (462 pages) : illustrations

Other Title:

Regression and linear modeling

Place of Publication:

Los Angeles, CA : SAGE Publications, Inc, 2017.

Summary:

In a conversational tone, Regression and Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Notes:

Includes bibliographical references and index.

Description based on XML content.

Other Format:

Print version :

ISBN:

9781071802724 (ebook) :

OCLC:

1136122004

Access Restriction:

Restricted for use by site license.