This book presents a wide range of topics to address the needs of several groups of users of rapidly growing methods of generalized linear models. Since the introduction of the idea of generalized linear mo...Lasīt vairāk
This is the first book on an evaluation of (weak) consistency of an information criterion for variable selection in high-dimensional multivariate linear regression models by using the high-dimensional asymptotic framework. It is an asymptotic fram...Lasīt vairāk
For advanced undergraduate or non-major graduate students in Advanced Statistical Modeling or Regression II and courses in Generalized Linear Models, Longitudinal Data Analysis, Correlated Data, Multilevel Models. Material on R at the end of each cha...Lasīt vairāk
This book presents an introduction to linear modeling using the generalized linear mixed model (GLMM) as an overarchingconceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear mode...Lasīt vairāk
This book is designed as a textbook for graduate students and as a resource for researchers seeking a thorough mathematical treatment of its subject. It develops the main results of regression and the analysis of variance, as well as the central resu...Lasīt vairāk
This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is...Lasīt vairāk
General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introduci...Lasīt vairāk
(Izdošanas datums: 29-Jun-2023, Hardback, Izdevniecība: Cambridge University Press, ISBN-13: 9781009322171)
General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introduci...Lasīt vairāk
Research on mixed models has been extensive over the most recent decade. This book differs from the authors previous monographs on longitudinal data in that it focuses on mixed models of a linear, generalized linear and nonlinear type. The book p...Lasīt vairāk
This book provides a unifying framework which can be used to apply many types of linear models used in applications to the analysis of data generated by scientific experiments....Lasīt vairāk
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated...Lasīt vairāk
(Izdošanas datums: 20-Jan-2023, Loose-leaf, Izdevniecība: OM Books International, ISBN-13: 9781265875855)
The idea for this book grew out of discussions between the statistics faculty and the engineering faculty at the Colorado School of Mines regarding our introductory statistics course for engineers. Our engineering faculty felt that the students need...Lasīt vairāk
This book is designed as a textbook for graduate students and as a resource for researchers seeking a thorough mathematical treatment of its subject. It develops the main results of regression and the analysis of variance, as well as the central resu...Lasīt vairāk
This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is...Lasīt vairāk
The third edition provides a comprehensive update of the available tools for fitting linear mixed-effects models in the newest versions of SAS, SPSS, R, Stata, and HLM. There is a focus on new tools for visualization of results and interpretation. Ne...Lasīt vairāk
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients in hospitals, or employees in firms. Longitudinal data are also cl...Lasīt vairāk
