We offer these texts bundled together at a discount for your students.Harry J. Khamis, The Association Graph and the Multigraph for Loglinear Models Volume 167This practical guide teaches nonstatistic
Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (str
Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the ba
Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has becom
Damodar N. Gujarati’s Linear Regression: A Mathematical Introduction presents linear regression theory in a rigorous, but approachable manner that is accessible to students in all social science
The factorial survey method is well established in the social sciences as a method of assessing respondents’ beliefs about the world, judgment principles, or decision rules. Instead of single-item que
Multilevel Structural Equation Modeling, by Silva, Bosancianu, and Littvay focuses on the confluence of two fields in applied statistics: multilevel modeling (MLM) and structural equation mo
Spatial Regression Models, 2nd ed. illustrates the use of spatial analysis in the social sciences within a regression framework. The book is accessible to readers without prior background in spat
A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treat
Sociologists Paxton (U. of Texas-Austin), John R. Hipp (U. of California-Irvine), and Sandra Marquart-Pyatt (Michigan State U.) explain methods appropriate to analyze nonrecursive simultaneous equatio
Understanding Regression Analysis: An Introductory Guide presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates
Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving r
Social Network Analysis, Third Edition succinctly illustrates the concepts and methods related to substantive social network research problems. The authors convey key material while at the same time m
Carol A. Chapelle shows readers how to design validation research for tests of human capacities and performance. Any test that is used to make decisions about people or programs should have undergone
Gathering Social Network Data provides an important complement to existing books that focus on social network analysis, and offers more detailed coverage than is available in existing chapter-length t
Generalized Linear Models by Jeff Gill and Michelle Torres explains the theoretical underpinnings of these models so that researchers can decide how to select the best way to adapt their data for this
This book of worked-out examples not only accompanies Timothy M. Hagle's earlier bookBasic Math for Social Scientists: Concepts, but also provides an informal refresher course in algebra sets, limits
