Minggu, 22 April 2012

Missing Data in Longitudinal Studies Pdf

Missing Data in Longitudinal Studies
Author: Michael J. Daniels
Edition: 1
Binding: Hardcover
ISBN: 1584886099

Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. Download Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) from rapidshare, mediafire, 4shared. To illustrate these methods, the authors employ several data sets throughout that cover a range of study designs, variable types, and missing data issues. The book first reviews modern approaches to formulate and interpret regression models for longitudinal data. It then discusses key ideas in Bayesian inference, including specifying prior distributions, computing posterior distribution, and assessing model fit. The book carefully describes th Search and find a lot of medical books in many category availabe for free download. Missing Data in Longitudinal Studies medical books pdf for free. The book carefully describes th



download

Related books


Statistical Analysis with Missing Data (Wiley Series in Probability and Statistics)


Praise for the First Edition of Statistical Analysis with Missing Data"An important contribution to the applied statistics literature.... I give the book high marks for unifying and making accessible much of the past and current work in this importan

Flexible Imputation of Missing Data (Chapman & Hall/CRC Interdisciplinary Statistics)


Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science-multiple imputation-fills gaps in the data with plausible valu

Missing Data in Clinical Studies (Statistics in Practice)


Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a crit

Discovering Structural Equation Modeling Using Stata


Discovering Structural Equation Modeling Using Stata is devoted to Stata's sem command and all it can do. You'll learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equati

Tidak ada komentar:

Posting Komentar