Name: Missing Data: Analysis and Design (en Inglés)
Price: 557.71 PEN
Availability: InStock
Author: Graham, John W.
ISBN: 9781489995735

portada Missing Data: Analysis and Design (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Graham, John W.

Idioma

Inglés

N° páginas

324

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.8 cm

Peso

0.49 kg.

ISBN13

9781489995735

Categorías

Investigación social y estadística
Investigación médica
Epidemiología y estadística médica
Probabilidad y estadística

Missing Data: Analysis and Design (en Inglés)

Graham, John W. (Autor) · Springer · Tapa Blanda

Libro Nuevo

S/ 557,71

S/ 929,51

Ahorras: S/ 371,81

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Missing Data: Analysis and Design (en Inglés)"

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 analysis 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 advancedreaders to expand their skill set.