BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary Statistics)

Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary Statistics)

Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary
Stock photo: cover may vary

Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary Statistics) Hardback - 2015

by Raghunathan, Trivellore

Add to wish list
  • Used
  • Good
  • Hardback
Used - Good

Description

hardcover. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book.
Ask the seller a question Add to wish list
A$223.75
Free Delivery within USA
Standard delivery: 7 to 14 days
More delivery options
Dropship order
Ships from Bonita (California, United States)

Details

  • Title Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary Statistics)
  • Author Raghunathan, Trivellore
  • Binding Hardback
  • Condition Used - Good
  • Pages 230
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2015-10-28
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # 1482211920.G
  • ISBN 9781482211924 / 1482211920
  • Weight 0.9 lbs (0.41 kg)
  • Dimensions 9.2 x 6.2 x 0.6 in (23.37 x 15.75 x 1.52 cm)
  • Category Mathematics
  • Library of Congress subjects Mathematical statistics, Missing observations (Statistics)
  • Library of Congress Catalogue Number 2016302652
  • Dewey Decimal Code 519.5
  • Quantity available 1

About Bonita California, United States

Biblio member since 2020

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Bonita

Reader reviews for Missing Data Analysis in Practice (Chapman & Hall/CRC Interdisciplinary Statistics)

From the publisher

Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings. Drawing on his 25 years of experience researching, teaching, and consulting in quantitative areas, the author presents both frequentist and Bayesian perspectives. He describes easy-to-implement approaches, the underlying assumptions, and practical means for assessing these assumptions. Actual and simulated data sets illustrate important concepts, with the data sets and codes available online.

The book underscores the development of missing data methods and their adaptation to practical problems. It mainly focuses on the traditional missing data problem. The author also shows how to use the missing data framework in many other statistical problems, such as measurement error, finite population inference, disclosure limitation, combing information from multiple data sources, and causal inference.

About the author

Trivellore Raghunathan is the director of the Survey Research Center in the Institute for Social Research and professor of biostatistics in the School of Public Health at the University of Michigan. He has published numerous papers in a range of statistical and public health journals. His research interests include applied regression analysis, linear models, design of experiments, sample survey methods, and Bayesian inference.

tracking-