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Interaction Effects in Linear and Generalized Linear Models
"This book is remarkable in its accessible treatment of interaction effects. Although this concept can be challenging for students (even those with some background in statistics), …
Regression Models for Categorical and Limited Dependent Variables
THE APPROACH "J. Scott Long's approach is one that I highly commend. There is a decided emphasis on the application and interpretation of the specific statistical techniques. Long …
Hierarchical Linear Models
"This is a first-class book dealing with one of the most important areas of current research in applied statistics…the methods described are widely applicable…the standard of …
Log-Linear Models for Event Histories
Event history analysisùa method for explaining why some people are more likely to experience a particular event, transition, or change than other peopleùhas been useful in the …
Propensity Score Analysis
Fully updated to reflect the most recent changes in the field, the Second Edition of Propensity Score Analysis provides an accessible, systematic review of the origins, history, …
Multivariate Taxometric Procedures
Can taxometric procedures be used to distinguish types (species, latent classes, taxa) from continua (dimensions, latent traits, factors); and, if so, how? Aimed at demystifying …
Multivariate Analysis of Categorical Data: Applications
A bonus is the insightful introduction by series editor Jan de Leeuw, putting applied statistics into perspective, blurring the somewhat artificial distinction between exploratory …
Structural Equation Modeling
Using detailed, empirical examples, Structural Equation Modeling, Second Edition, presents a thorough and sophisticated treatment of the foundations of structural equation modeling …
Regression Analysis
Berk has incisively identified the various strains of regression abuse and suggests practical steps for researchers who desire to do good social science while avoiding such …
Latent Class and Discrete Latent Trait Models
The standard latent class model. It has been popular among social scientists as an instrument for data reduction, as a flexible tool for analyzing structural relationships between …
Models for Social Networks With Statistical Applications
Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze …
Spatial Regression Models for the Social Sciences
Spatial Regression Models for the Social Sciences shows researchers and students how to work with spatial data without the need for advanced mathematical statistics. Focusing on …