𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Linear Mixed Models in Practice: A SAS-Oriented Approach

✍ Scribed by Geert Verbeke, Geert Molenberghs (auth.)


Publisher
Springer-Verlag New York
Year
1997
Tongue
English
Leaves
318
Series
Lecture Notes in Statistics 126
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


The dissemination of the MIXED procedure in SAS has provided a whole class of statistical models for routine use. We believe that both the ideas beΒ­ hind the techniques and their implementation in SAS are not at all straightΒ­ forward and users from various applied backgrounds, including the pharΒ­ maceutical industry, have experienced difficulties in using the procedure effectively. Courses and consultancy on PROC MIXED have been in great demand in recent years, illustrating the clear need for resource material to aid the user. This book is intended as a contribution to bridging this gap. We hope the book will be of value to a wide audience, including applied statisticians and many biomedical researchers, particularly in the pharmaΒ­ ceutical industry, medical and public health research organizations, conΒ­ tract research organizations, and academic departments. This implies that our book is explanatory rather than research oriented and that it emphaΒ­ sizes practice rather than mathematical rigor. In this respect, clear guidance and advice on practical issues are the main focus of the text. Nevertheless, this does not imply that more advanced topics have been avoided. Sections containing material of a deeper level have been sign posted by means of an asterisk.

✦ Table of Contents


Front Matter....Pages i-xv
Introduction....Pages 1-9
An Example-Based Tour in Linear Mixed Models....Pages 11-61
Linear Mixed Models for Longitudinal Data....Pages 63-153
Case Studies....Pages 155-189
Linear Mixed Models and Missing Data....Pages 191-274
Back Matter....Pages 275-308

✦ Subjects


Statistics for Life Sciences, Medicine, Health Sciences


πŸ“œ SIMILAR VOLUMES


Linear Mixed Models: A Practical Guide U
✍ Brady T. West, Kathleen B. Welch, Andrzej T Galecki πŸ“‚ Library πŸ“… 2006 πŸ› Chapman and Hall/CRC 🌐 English

Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), <b>Linear Mixed Models: A Practical Guide Using Statistical Software</b> provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of

Linear Mixed Models: A Practical Guide U
✍ Brady T. West; Kathleen B. Welch; Andrzej T Galecki πŸ“‚ Library πŸ“… 2022 πŸ› CRC Press 🌐 English

Highly recommended by JASA, Technometrics, and other leading statistical journals, the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, T

Linear Mixed Models A Practical Guide Us
✍ Brady West, Kathleen B. Welch, Andrzej T Galecki πŸ“‚ Library πŸ“… 2006 πŸ› Chapman and Hall/CRC 🌐 English

Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of cluste

Linear models: A mean model approach
✍ Barry Kurt Moser πŸ“‚ Library πŸ“… 1996 πŸ› AP 🌐 English

Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. <b>Linear Models examines the subject from a mean model perspective, defining simple and easy-to-learn rules for building mean models, regression models, mean

Linear Models: A Mean Model Approach
✍ Barry Kurt Moser πŸ“‚ Library πŸ“… 1996 πŸ› Academic Press 🌐 English

Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. <b>Linear Models</b> examines the subject from a mean model perspective, defining simple and easy-to-learn rules for building mean models, regression models, me