Generalized, Linear, and Mixed Models, 2nd Edition

Charles E. McCulloch, PhD, is Professor and Head of the Division of Biostatistics in the School of Medicine at the University of California, San Francisco. A Fellow of the American Statistical Association, Dr. McCulloch is the author of numerous published articles in the areas of longitudinal data analysis, generalized linear mixed models, and latent class models and their applications.

Shayle R. Searle, PhD, is Professor Emeritus in the Department of Biological Statistics and Computational Biology at Cornell University. Dr. Searle is the author of Linear Models, Linear Models for Unbalanced Data, Matrix Algebra Useful for Statistics, and Variance Components, all published by Wiley.

John M. Neuhaus, PhD, is Professor of Biostatistics in the School of Medicine at the University of California, San Francisco. A Fellow of the American Statistical Association and the Royal Statistical Society, Dr. Neuhaus has authored or coauthored numerous journal articles on statistical methods for analyzing correlated response data and assessments on the effects of statistical model misspecification.