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.
