Methods And Applications Of Linear Models

Download Methods And Applications Of Linear Models full books in PDF, epub, and Kindle. Read online free Methods And Applications Of Linear Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Regression Analysis and Linear Models

Regression Analysis and Linear Models
Author :
Publisher : Guilford Publications
Total Pages : 689
Release :
ISBN-10 : 9781462527984
ISBN-13 : 1462527981
Rating : 4/5 (981 Downloads)

Book Synopsis Regression Analysis and Linear Models by : Richard B. Darlington

Download or read book Regression Analysis and Linear Models written by Richard B. Darlington and published by Guilford Publications. This book was released on 2016-08-22 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.


Regression Analysis and Linear Models Related Books

Regression Analysis and Linear Models
Language: en
Pages: 689
Authors: Richard B. Darlington
Categories: Social Science
Type: BOOK - Published: 2016-08-22 - Publisher: Guilford Publications

DOWNLOAD EBOOK

Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the soci
Linear Models in Statistics
Language: en
Pages: 690
Authors: Alvin C. Rencher
Categories: Mathematics
Type: BOOK - Published: 2008-01-07 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizati
Generalized Linear Mixed Models
Language: en
Pages: 547
Authors: Walter W. Stroup
Categories: Mathematics
Type: BOOK - Published: 2016-04-19 - Publisher: CRC Press

DOWNLOAD EBOOK

With numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching
Hierarchical Linear Models
Language: en
Pages: 294
Authors: Anthony S. Bryk
Categories: Mathematics
Type: BOOK - Published: 1992 - Publisher: SAGE Publications, Incorporated

DOWNLOAD EBOOK

Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and
Regression & Linear Modeling
Language: en
Pages: 489
Authors: Jason W. Osborne
Categories: Psychology
Type: BOOK - Published: 2016-03-24 - Publisher: SAGE Publications

DOWNLOAD EBOOK

In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become fa