Logo - springer
Slogan - springer

Statistics - Social Sciences & Law | Missing Data - Analysis and Design

Missing Data

Analysis and Design

Graham, John W.

2012, XXIV, 324 p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$99.00

(net) price for USA

ISBN 978-1-4614-4018-5

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase


learn more about Springer eBooks

add to marked items

Hardcover
Information

Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$129.00

(net) price for USA

ISBN 978-1-4614-4017-8

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$129.00

(net) price for USA

ISBN 978-1-4899-9573-5

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • Enables non-statisticians to implement modern missing data procedures properly in their research
  • Contains easy-to-read information for readers of all levels
  • Utilizes an accompanying website

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.

Content Level » Research

Keywords » Data analysis - Missing data - Monte Carlo - Multilevel data - Multiple imputation

Related subjects » Life Sciences, Medicine & Health - Social Sciences & Law - Statistics

Table of contents / Preface / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.