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Longitudinal data analysis using structural equation models

Longitudinal data analysis using structural equation models

자료유형
단행본
서명 / 저자사항
Longitudinal data analysis using structural equation models / John J. McArdle and John R. Nesselroade.
발행사항
Washington, D.C. : American Psychological Association, 2014.
형태사항
xi, 426 p. : ill. ; 26 cm.
ISBN
9781433817151 1433817152
내용주기
Preface -- Overview -- Foundations -- Background and goals of longitudinal research -- Basics of structural equation modeling -- Some technical details on structural equation modeling -- Using the simplified ram notation -- Benefits and problems of longitudinal structure modeling -- The first purpose of LSEM : direct identification of intra-individual changes -- Alternative definitions of individual changes -- Analyses based on latent curve models (LCM) -- Analyses based on time series regression (TSR) -- Analyses based on latent change score (LCS) models -- Analyses based on advanced latent change score models -- The second purpose of LSEM : identification of inter-individual differences in intra-individual changes -- Studying inter-individual differences in intra-individual changes -- Repeated measures analysis of variance as a structural model -- Multi-level structural equation modeling approaches to group differences -- Multi-group structural equation modeling approaches to group differences -- Incomplete data with multiple group modeling of changes -- The third purpose of LSEM : identification of inter-relationships in growth -- Considering common factors/latent variables in models -- Considering factorial invariance in longitudinal SEM -- Alternative common factors with multiple longitudinal observations -- More alternative factorial solutions for longitudinal data -- Extensions to longitudinal categorical factors -- The fourth purpose of LSEM : identification of causes (determinants) of intra-individual changes -- Analyses based on cross-lagged regression and changes -- Analyses based on cross-lagged regression in changes of factors -- Current models for multiple longitudinal outcome scores -- The bivariate latent change score model for multiple occasions -- Plotting bivariate latent change score results -- The fifth purpose of lsem : identification of inter-individual differences in causes (determinants) of intra-individual changes -- Dynamic processes over groups -- Dynamic influences over groups -- Applying a bivariate change model with multiple groups -- Notes on the inclusion of randomization in longitudinal studies -- The popular repeated measures analysis of variance -- Summary and discussion -- Contemporary data analyses based on planned incompleteness -- Factor invariance in longitudinal research -- Variance components for longitudinal factor models -- Models for intensively repeated measures -- CODA : the future is yours! -- References.
서지주기
Includes bibliographical references (p. 373-400) and index.
일반주제명
Longitudinal method. Psychology -- Research.
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020 ▼a 9781433817151
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050 0 0 ▼a BF76.6.L65 ▼b M33 2014
082 0 0 ▼a 150.72/1 ▼2 23
084 ▼a 150.721 ▼2 DDCK
090 ▼a 150.721 ▼b M115L
100 1 ▼a McArdle, John J.
245 1 0 ▼a Longitudinal data analysis using structural equation models / ▼c John J. McArdle and John R. Nesselroade.
260 ▼a Washington, D.C. : ▼b American Psychological Association, ▼c 2014.
300 ▼a xi, 426 p. : ▼b ill. ; ▼c 26 cm.
504 ▼a Includes bibliographical references (p. 373-400) and index.
505 0 0 ▼g Preface -- Overview -- Foundations -- Background and goals of longitudinal research -- ▼t Basics of structural equation modeling -- ▼t Some technical details on structural equation modeling -- ▼t Using the simplified ram notation -- ▼t Benefits and problems of longitudinal structure modeling -- ▼t The first purpose of LSEM : direct identification of intra-individual changes -- ▼t Alternative definitions of individual changes -- ▼t Analyses based on latent curve models (LCM) -- ▼t Analyses based on time series regression (TSR) -- ▼t Analyses based on latent change score (LCS) models -- ▼t Analyses based on advanced latent change score models -- ▼t The second purpose of LSEM : identification of inter-individual differences in intra-individual changes -- ▼t Studying inter-individual differences in intra-individual changes -- ▼t Repeated measures analysis of variance as a structural model -- ▼t Multi-level structural equation modeling approaches to group differences -- ▼t Multi-group structural equation modeling approaches to group differences -- ▼t Incomplete data with multiple group modeling of changes -- ▼t The third purpose of LSEM : identification of inter-relationships in growth -- ▼t Considering common factors/latent variables in models -- ▼t Considering factorial invariance in longitudinal SEM -- ▼t Alternative common factors with multiple longitudinal observations -- ▼t More alternative factorial solutions for longitudinal data -- ▼t Extensions to longitudinal categorical factors -- ▼t The fourth purpose of LSEM : identification of causes (determinants) of intra-individual changes -- ▼t Analyses based on cross-lagged regression and changes -- ▼t Analyses based on cross-lagged regression in changes of factors -- ▼t Current models for multiple longitudinal outcome scores -- ▼t The bivariate latent change score model for multiple occasions -- ▼t Plotting bivariate latent change score results -- ▼t The fifth purpose of lsem : identification of inter-individual differences in causes (determinants) of intra-individual changes -- ▼t Dynamic processes over groups -- ▼t Dynamic influences over groups -- ▼t Applying a bivariate change model with multiple groups -- ▼t Notes on the inclusion of randomization in longitudinal studies -- ▼t The popular repeated measures analysis of variance -- ▼t Summary and discussion -- ▼t Contemporary data analyses based on planned incompleteness -- ▼t Factor invariance in longitudinal research -- ▼t Variance components for longitudinal factor models -- ▼t Models for intensively repeated measures -- ▼t CODA : the future is yours! -- References.
650 0 ▼a Longitudinal method.
650 0 ▼a Psychology ▼x Research.
700 1 ▼a Nesselroade, John R.
740 0 2 ▼a First purpose of LSEM : direct identification of intra-individual changes.
740 0 2 ▼a Second purpose of LSEM : identification of inter-individual differences in intra.
740 0 2 ▼a Third purpose of LSEM : identification of inter-relationships in growth.
740 0 2 ▼a Fourth purpose of LSEM : identification of causes (determinants) of intra-individual changes.
740 0 2 ▼a Bivariate latent change score model for multiple occasions.
740 0 2 ▼a Fifth purpose of lsem : identification of inter-individual differences in causes (determinants) of intra-individual changes.
740 0 2 ▼a Popular repeated measures analysis of variance.
945 ▼a KLPA

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No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 150.721 M115L 등록번호 111724393 도서상태 대출가능 반납예정일 예약 서비스 B M

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