Primer  of Applied Regression & Analysis of Variance
Publisher: McGraw-Hill Education
Published: April 8, 2016
Place of publication: New York, USA
Format: Hardcover
Number of pages: 1183
ISBN-13: 9780071824118
Description: Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been acclaimed for its user-friendly style that makes complicated material understandable to readers who do not have an extensive math background.

The text is packed with learning aids that include chapter-ending summaries and end-of-chapter problems that quickly assess mastery of the material. Examples from biological and health sciences are included to clarify and illustrate key points. The techniques discussed apply to a wide range of disciplines, including social and behavioral science as well as health and life sciences. Typical courses that would use this text include those that cover multiple linear regression and ANOVA.

Four completely new chapters
Completely updated software information and examples
Notes: Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods.
Table of contents: title: Why do multivariate analysis? --; title: The first step : understanding simple linear regression --; title: Regression with two or more independent variables --; title: Do the data fit the assumptions? --; title: Multicollinearity and what to do about it --; title: Selecting the "best" regression model --; title: Missing data --; title: One-way analysis of variance --; title: Two-way analysis of variance --; title: Repeated measures --; title: Mixing continuous and categorical variables : analysis of covariance --; title: Regression with a qualitative dependent variable : logistic regression --; title: Regression modeling of time-to-event data : survival analysis --; title: Nonlinear regression.