+612 9045 4394
Computational Methods in Biomedical Research : Biostatistics Series 24 - Ravindra Khattree

Computational Methods in Biomedical Research

Biostatistics Series 24

By: Ravindra Khattree (Editor), Dayanand Naik (Editor)

Sorry, the book that you are looking for is not available right now.

We did a search for other books with a similar title, however there were no matches. You can try selecting from a similar category, click on the author's name, or use the search box above to find your book.

Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computational statistical methods that are used in biomedical research.

Written by active researchers in the field, this authoritative collection covers a wide range of topics. It introduces each topic at a basic level, before moving on to more advanced discussions of applications. The book begins with microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. It then uses state space models to predict US cancer mortality rates and provides an overview of the application of multistate models in analyzing multiple failure times. The book also describes various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, and the classification rules for repeated measures data. The volume concludes with estimation methods for analyzing longitudinal data.

Supplying the knowledge necessary to perform sophisticated statistical analyses, this reference is a must-have for anyone involved in advanced biomedical and pharmaceutical research. It will help in the quest to identify potential new drugs for the treatment of a variety of diseases.

Microarray Data Analysis
Machine Learning Techniques for Bioinformatics: Fundamentals and Applications
Machine Learning Methods for Cancer Diagnosis and Prognostication
Protein Profiling for Disease Proteomics with Mass Spectrometry: Computational Challenges
Predicting US Cancer Mortality Counts Using State Space Models
Analyzing Multiple Failure Time Data Using SAS
Mixed-Effects Models for Longitudinal Virologic and Immunologic HIV Data
Bayesian Computational Methods in Biomedical Research
Sequential Monitoring of Randomization Tests
Proportional Hazards Mixed-Effects Models and Applications
Classification Rules for Repeated Measures Data from Biomedical Research
Estimation Methods for Analyzing Longitudinal Data Occurring in Biomedical Research
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9781584885771
ISBN-10: 1584885777
Series: Biostatistics Series 24
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 432
Published: 12th December 2007
Country of Publication: US
Dimensions (cm): 24.77 x 17.15  x 2.54
Weight (kg): 0.75
Edition Number: 1