This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzin

Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with a helpful guide to conducting multilevel data modeling us