A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be.
Table of contents
- Applied Mixed Models in Medicine
- Applied Mixed Models in Medicine : Helen Brown :
- Bestselling Series
- Related Resources
- Applied Mixed Models in Medicine, 3rd Edition
Product details Format Hardback pages Dimensions x x 33mm People who bought this also bought. Statistical Intervals Luis A. Matrix Algebra James E. Reasoning with Data Jeffrey M. Meta-Analysis with R Guido Schwarzer.
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Applied Mixed Models in Medicine
The Ghost Map Steven Johnson. Clinical Epidemiology Diederick E. Essential Biostatistics Harvey Motulsky. Difference and Disease Suman Seth.
Applied Mixed Models in Medicine : Helen Brown :
Media and Suicide Steven Stack. Human Molecular Genetics Tom Strachan. Anatomy of an Epidemic Ken Kliban. A Dictionary of Epidemiology Miquel Porta. Plagues and People William McNeill. Occupational and Environmental Health Barry S.
Bestselling Series
Applied Predictive Modeling Kjell Johnson. Health Impact Assessment Jayne Parry. Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists. Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output.
Related Resources
Supported by a website featuring computer code, data sets, and further material. A Multi-Centre Trial 5.
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- Applied Mixed Models in Medicine - Helen Brown, Robin Prescott - Google Книги.
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Meta-analysis 6 Repeated Measures Data 6. Covariance Pattern Models for Normal Data 6. Covariance Pattern Models for Count Data 6.
There have been many recent advances in mixed modelling, particularly regarding the software and applications. This new edition of a groundbreaking text discusses the latest developments, from updated SAS techniques to the increasingly wide range of applications.
Applied Mixed Models in Medicine, 3rd Edition
This much-anticipated second edition is ideal for applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The text will also be of great value to a broad range of scientists, particularly those working the medical and pharmaceutical areas. Prescott, University of Edinburgh, UK. KGaA - Provider - www. Short Description Since the publication of the first edition--which was very well received--the topic of mixed modeling has seen many developments, particularly regarding software and applications.