Multiple Imputation with Structural Equation Modeling : Using auxiliary variables when data are missing

Language: English

Published by LAP LAMBERT Academic Publishing, 2013

3659435821 / 9783659435829

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Even very well-designed, well-executed research can result in missing responses at any rate, particularly in survey research. This Monte Carlo study investigated the effectiveness of the inclusive strategy with incomplete data, in a structural equation modeling framework with multiple imputation. Specifically, the study examined the influence of sample size, missing rates, various missingness mechanism combinations, and the inclusive strategy on convergence failure, bias, standard error, and confidence interval coverage of parameters, and model fit. The inclusive strategy, which includes additional variables in the imputation model, was found to improve parameter estimation in most cases, particularly with the convex type of missingness and the nonignorable cases caused by MAR(missing at random) and the restrictive strategy. Implications and future directions are discussed. SAS macro programs are attached.

Seller Inventory # 9783659435829

Title
Multiple Imputation with Structural Equation Modeling : Using auxiliary variables when data are missing
Author
Jin Eun Yoo
Publisher
LAP LAMBERT Academic Publishing
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659435821
ISBN 13
9783659435829
Item weight
209 grams
Dimensions
220x150x9 mm

AHA-BUCH GmbH

Einbeck, Germany

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AbeBooks seller since August 14, 2006

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