Regression & Linear Modeling: Best Practices and Modern Methods

✍ Scribed by Jason W. Osborne

• Publisher: SAGE Publications, Incorporated
• Year: 2016
• Tongue: English
• Leaves: 489
• Category: Library

✦ Synopsis

In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

✦ Table of Contents

REGRESSION & LINEAR MODELING- FRONT COVER
REGRESSION & LINEAR MODELING
COPYRIGHT
BRIEF CONTENTS
DETAILED CONTENTS
PREFACE
ACKNOWLEDGMENTS
ABOUT THE AUTHOR
CHAPTER 1- A NERDLY MANIFESTO
CHAPTER 2- BASIC ESTIMATION AND ASSUMPTIONS
CHAPTER 3- SIMPLE LINEAR MODELS WITH CONTINUOUS DEPENDENT VARIABLES: SIMPLE REGRESSION ANALYSES
CHAPTER 4- SIMPLE LINEAR MODELS WITH CONTINUOUS DEPENDENT VARIABLES: SIMPLE ANOVA ANALYSES
CHAPTER 5- SIMPLE LINEAR MODELS WITH CATEGORICAL DEPENDENT VARIABLES: BINARY LOGISTIC REGRESSION
CHAPTER 6- SIMPLE LINEAR MODELS WITH POLYTOMOUS CATEGORICAL DEPENDENT VARIABLES: MULTINOMIAL AND ORDINAL LOGISTIC REGRESSION
CHAPTER 7- SIMPLE CURVILINEAR MODELS
CHAPTER 8- MULTIPLE INDEPENDENT VARIABLES
CHAPTER 9- INTERACTIONS BETWEEN INDEPENDENT VARIABLES: SIMPLE MODERATION
CHAPTER 10- CURVILINEAR INTERACTIONS BETWEEN INDEPENDENT VARIABLES
CHAPTER 11- POISSON MODELS: LOW-FREQUENCY COUNT DATA AS DEPENDENT VARIABLES
CHAPTER 12- LOG-LINEAR MODELS: GENERAL LINEAR MODELS WHEN ALL OF YOUR VARIABLES ARE UNORDERED CATEGORICAL
CHAPTER 13- A BRIEF INTRODUCTION TO HIERARCHICAL LINEAR MODELING
CHAPTER 14- MISSING DATA IN LINEAR MODELING
CHAPTER 15- TRUSTWORTHY SCIENCE: IMPROVING STATISTICAL REPORTING
CHAPTER 16- RELIABLE MEASUREMENT MATTERS
CHAPTER 17- PREDICTION IN THE GENERALIZED LINEAR MODEL
CHAPTER 18- MODELING IN LARGE, COMPLEX SAMPLES: THE IMPORTANCE OF USING APPROPRIATE WEIGHTS AND DESIGN EFFECT COMPENSATION
APPENDIX A- A BRIEF USER’S GUIDE TO Z-SCORES
AUTHOR INDEX
SUBJECT INDEX