Regression Analysis For Social Sciences by Alexander Von EyeRegression Analysis For Social Sciences by Alexander Von Eye

Regression Analysis For Social Sciences

byAlexander Von Eye, Christof SchusterEditorAlexander Von Eye

Paperback | June 25, 1998

Pricing and Purchase Info

$188.73 online 
$208.07 list price save 9%
Earn 944 plum® points
Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

Regression Analysis for Social Sciencespresents methods of regression analysis in an accessible way, with each method having illustrations and examples. A broad spectrum of methods are included: multiple categorical predictors, methods for curvilinear regression, and methods for symmetric regression. This book can be used for courses in regression analysis at the advanced undergraduate and beginning graduate level in the social and behavioral sciences. Most of the techniques are explained step-by-step enabling students and researchers to analyze their own data. Examples include data from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text.

  • Presents accessible methods of regression analysis
  • Includes a broad spectrum of methods
  • Techniques are explained step-by-step
  • Provides sample command and result files for SYSTAT
Title:Regression Analysis For Social SciencesFormat:PaperbackDimensions:386 pages, 9 × 6 × 0.68 inPublished:June 25, 1998Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0127249559

ISBN - 13:9780127249551

Look for similar items by category:

Reviews

Table of Contents

Simple Linear Regression
Multiple Linear Regression
Categorical Predictors
Outlier Analysis
Residual Analysis
Polynomial Regression
Multicollinearity
Multiple Curvilinear Regression
Interaction Terms in Regression
Robust Regression
Symmetric Regression
Variable Selection Techniques
Regression for Longitudinal Data
Piecewise Regression
Dichotomous Criterion Variables
Computational Issues
Elements of Matrix Algebra
Basics of Differentiation
Basics of Vector Differentiation
Polynomials
Data Sets

Editorial Reviews

"Individuals in the social and behavioral sciences as well as those with biological and biometrical backrounds would benefit from this book. Recommended. Upper-division undergraduates through faculty."
--D.J. Gougeon, University of Scranton, in CHOICE, February 1999