Shortcuts
Top of page (Alt+0)
Page content (Alt+9)
Page menu (Alt+8)
Your browser does not support javascript, some WebOpac functionallity will not be available.
.
Default
.
PageMenu
-
Main Menu
-
Simple Search
.
Advanced Search
.
Journal Search
.
Refine Search Results
.
Preferences
.
Search Menu
Simple Search
.
Advanced Search
.
New Items Search
.
Journal Search
.
Refine Search Results
.
Bottom Menu
Help
Italian
.
English
.
German
.
New Item Menu
New Items Search
.
New Items List
.
Links
SISSA Library
.
ICTP library
.
Italian National web catalog (SBN)
.
Trieste University web catalog
.
Udine University web catalog
.
© LIBERO v6.4.1sp220816
Page content
You are here
:
Catalogue Tag Display
Catalogue Tag Display
MARC 21
Missing Data: Analysis and Design /
Tag
Description
020
$a9781461440185
082
$a519.5
099
$aOnline Resource: Springer
100
$aGraham, John W.
245
$aMissing Data$h[Ebook]$bAnalysis and Design$cby John W. Graham.
260
$aNew York, NY$bSpringer
260
$c2012.
300
$aXIX, 323 pages: 27 illus., 19 illus. in color.$bonline resource.
336
$atext
338
$aonline resource
440
$aStatistics for Social and Behavioral Sciences
505
$a
Missing Data Theory -- Multiple Imputation and Basic Analysis -- Practical Issues in Missing Data Analysis -- Planned Missing Data Design.
520
$a
Missing data have long plagued those conducting applied research in the social, behavioral, and health sciences. Good missing data analysis solutions are available, but practical information about implementation of these solutions has been lacking. The objective of Missing Data: Analysis and Design is to enable investigators who are non-statisticians to implement modern missing data procedures properly in their research, and reap the benefits in terms of improved accuracy and statistical power. Missing Data: Analysis and Design contains essential information for both beginners and advanced readers For researchers with limited missing data analysis experience, this book offers an easy-to-read introduction to the theoretical underpinnings of analysis of missing data; provides clear, step-by-step instructions for performing state-of-the-art multiple imputation analyses; and offers practical advice, based on over 20 years' experience, for avoiding and troubleshooting problems. For more advanced readers, unique discussions of attrition, non-Monte-Carlo techniques for simulations involving missing data, evaluation of the benefits of auxiliary variables, and highly cost-effective planned missing data designs are provided. The author lays out missing data theory in a plain English style that is accessible and precise. Most analyses described in the book are conducted using the well-known statistical software packages SAS and SPSS, supplemented by Norm 2.03 and associated Java-based automation utilities. A related web site contains free downloads of the supplementary software, as well as sample empirical data sets and a variety of practical exercises described in the book to enhance and reinforce the reader's learning experience. Missing Data: Analysis and Design and its web site work together to enable beginners to gain confidence in their ability to conduct missing data analysis, and more advanced readers to expand their skill set. JOHN W. GRAHAM, PhD, is Professor of Biobehavioral Health at The Pennsylvania State University. His research and publishing focus on the evaluation of health promotion and disease prevention interventions. He specializes in evaluation research methods, including missing data analysis and design, structural equation modeling, and measurement.
538
$aOnline access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
710
$aSpringerLink (Online service)
830
$aStatistics for Social and Behavioral Sciences
856
$u
http://dx.doi.org/10.1007/978-1-4614-4018-5
Quick Search
Search for