Posted by **DZ123** at Dec. 14, 2015

English | 1997 | ISBN: 0412040611 | PDF | pages: 418 | 6 mb

Posted by **tanas.olesya** at April 6, 2015

English | Aug 1, 1997 | ISBN: 0412040611 | 514 Pages | PDF | 6 MB

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems.

Posted by **DZ123** at Sept. 14, 2014

English | 1997 | ISBN: 0412040611 | PDF | pages: 418 | 6 mb

Posted by **arundhati** at June 7, 2013

1997 | ISBN-10: 0412040611 | 444 pages | PDF | 6,8 MB

Posted by **kalyan1232008** at March 27, 2009

Chapman & Hall/CRC | English | ISBN- 0412040611 | August 1, 1997 | 430 pages | PDF | 5.7MB

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis. Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms.All techniques are illustrated with real data examples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.

Posted by **libr** at Oct. 29, 2017

English | 2014 | ISBN: 3319046446 | 91 pages | PDF | 3,8 MB

Posted by **nebulae** at Aug. 13, 2017

English | ISBN: 1439836590 | 2014 | 314 pages | PDF | 2 MB

Posted by **AvaxGenius** at July 26, 2017

English | PDF | 2017 | 257 Pages | ISBN : 9811037930 | 2.94 MB

This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes.

Posted by **hill0** at July 8, 2017

English | 13 Aug. 2017 | ISBN: 9811037930 | 250 Pages | PDF | 2.94 MB

This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data.

Posted by **hill0** at April 19, 2017

English | 10 Oct. 2013 | ISBN: 1461487145 | 288 Pages | EPUB | 3.06 MB

Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points. By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies,