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Regression Analysis And Linear Models Concepts Applications And Implementation 1st Edition Richard B Darlington Phd

  • SKU: BELL-5523936
Regression Analysis And Linear Models Concepts Applications And Implementation 1st Edition Richard B Darlington Phd
$ 31.00 $ 45.00 (-31%)

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Regression Analysis And Linear Models Concepts Applications And Implementation 1st Edition Richard B Darlington Phd instant download after payment.

Publisher: The Guilford Press
File Extension: PDF
File size: 7.6 MB
Pages: 661
Author: Richard B. Darlington PhD, Andrew F. Hayes PhD
ISBN: 9781462521135, 1462521134
Language: English
Year: 2016
Edition: 1

Product desciption

Regression Analysis And Linear Models Concepts Applications And Implementation 1st Edition Richard B Darlington Phd by Richard B. Darlington Phd, Andrew F. Hayes Phd 9781462521135, 1462521134 instant download after payment.

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 author's 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.

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