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The effects of missing time-varying ...

Bainter, Sierra A.

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The effects of missing time-varying covariates in multilevel models.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The effects of missing time-varying covariates in multilevel models./
Author:	Bainter, Sierra A.
Description:	74 p.
Notes:	Source: Masters Abstracts International, Volume: 51-06.
Contained By:	Masters Abstracts International51-06(E).
Subject:	Psychology, Psychometrics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1538010
ISBN:	9781303104602

The effects of missing time-varying covariates in multilevel models.
Bainter, Sierra A.

The effects of missing time-varying covariates in multilevel models. - 74 p.

Source: Masters Abstracts International, Volume: 51-06.

Thesis (M.A.)--The University of North Carolina at Chapel Hill, 2013.

Multilevel models are commonly used in psychological research to examine developmentally-motivated hypotheses concerning the within- and between-person effects of a time-varying covariate on some outcome. Whereas multilevel models are flexible to accommodate incomplete data on the outcome, missing time-varying covariates present significant challenges to researchers. Unless multiple imputation is used, missing time-varying covariates will lead to a loss of data. This project evaluated the effects of missing time-varying covariates and imputation of missing time-varying covariates in multilevel models using a multifaceted simulation study. My results showed that missing time-varying covariates can lead to biased parameter estimates. However this bias is likely minor compared to bias already present in complete data due to unreliable estimates of the person-mean of the time-varying covariate. The results presented here are clear motivation for researchers to choose alternative estimation strategies that can account for measurement error in the person mean, whether or not time-varying covariates are missing.

ISBN: 9781303104602Subjects--Topical Terms:

1017742
Psychology, Psychometrics.

The effects of missing time-varying covariates in multilevel models.
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020 $a 9781303104602
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100 1 $a Bainter, Sierra A. $3 2096030
245 1 4 $a The effects of missing time-varying covariates in multilevel models.
300 $a 74 p.
500 $a Source: Masters Abstracts International, Volume: 51-06.
500 $a Adviser: Patrick J. Curran.
502 $a Thesis (M.A.)--The University of North Carolina at Chapel Hill, 2013.
520 $a Multilevel models are commonly used in psychological research to examine developmentally-motivated hypotheses concerning the within- and between-person effects of a time-varying covariate on some outcome. Whereas multilevel models are flexible to accommodate incomplete data on the outcome, missing time-varying covariates present significant challenges to researchers. Unless multiple imputation is used, missing time-varying covariates will lead to a loss of data. This project evaluated the effects of missing time-varying covariates and imputation of missing time-varying covariates in multilevel models using a multifaceted simulation study. My results showed that missing time-varying covariates can lead to biased parameter estimates. However this bias is likely minor compared to bias already present in complete data due to unreliable estimates of the person-mean of the time-varying covariate. The results presented here are clear motivation for researchers to choose alternative estimation strategies that can account for measurement error in the person mean, whether or not time-varying covariates are missing.
590 $a School code: 0153.
650 4 $a Psychology, Psychometrics. $3 1017742
690 $a 0632
710 2 $a The University of North Carolina at Chapel Hill. $b Psychology. $3 1017867
773 0 $t Masters Abstracts International $g 51-06(E).
790 $a 0153
791 $a M.A.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1538010