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Missing data analysis in practice

Raghunathan, Trivellore.

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Missing data analysis in practice

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Missing data analysis in practice/ Trivellore Raghunathan.
作者:	Raghunathan, Trivellore.
出版者:	Boca Raton, FL :CRC Press, Taylor & Francis Group, : c2016.,
面頁冊數:	1 online resource (xix, 210 p.) :ill.
附註:	"A Chapman & Hall book"--title page.
內容註:	Basic concepts -- Weighting methods -- Imputation -- Multiple imputation -- Regression analysis -- Longitudinal analysis with missing values -- Nonignorable missing data mechanisms -- Other applications -- Other topics.
標題:	Mathematical statistics. -
電子資源:	https://www.taylorfrancis.com/books/9780429171673
ISBN:	9781482211931

Missing data analysis in practice
Raghunathan, Trivellore.

Missing data analysis in practice[electronic resource] /Trivellore Raghunathan. - 1st ed. - Boca Raton, FL :CRC Press, Taylor & Francis Group,c2016. - 1 online resource (xix, 210 p.) :ill. - Chapman & Hall/CRC interdisciplinary statistics series. - Interdisciplinary statistics..

"A Chapman & Hall book"--title page.

Includes bibliographical references (p. 187-203)

Basic concepts -- Weighting methods -- Imputation -- Multiple imputation -- Regression analysis -- Longitudinal analysis with missing values -- Nonignorable missing data mechanisms -- Other applications -- Other topics.

"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"--

ISBN: 9781482211931

LCCN: 2016302652Subjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276 / .R26 2015

Dewey Class. No.: 519.5

Missing data analysis in practice
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300 $a 1 online resource (xix, 210 p.) : $b ill.
490 1 $a Chapman & Hall/CRC interdisciplinary statistics series
500 $a "A Chapman & Hall book"--title page.
504 $a Includes bibliographical references (p. 187-203)
505 0 $a Basic concepts -- Weighting methods -- Imputation -- Multiple imputation -- Regression analysis -- Longitudinal analysis with missing values -- Nonignorable missing data mechanisms -- Other applications -- Other topics.
520 $a "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"-- $c Provided by publisher.
588 $a Description based on print version record.
650 0 $a Mathematical statistics. $3 516858
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