New methods for the analysis of change.
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Published By American Psychological Association

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Trait–state models for longitudinal data.

New methods for the analysis of change. ◽

10.1037/10409-008 ◽

2001 ◽

pp. 243-263 ◽

Cited By ~ 77

Author(s):

David A. Kenny ◽

Alex Zautra

Keyword(s):

Longitudinal Data ◽

State Models

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The role of factorial invariance in modeling growth and change.

New methods for the analysis of change. ◽

10.1037/10409-007 ◽

2001 ◽

pp. 203-240 ◽

Cited By ~ 124

Author(s):

William Meredith ◽

John Horn

Keyword(s):

Factorial Invariance ◽

Growth And Change ◽

Modeling Growth

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Second-order latent growth models.

New methods for the analysis of change. ◽

10.1037/10409-006 ◽

2001 ◽

pp. 179-200 ◽

Cited By ~ 60

Author(s):

Aline G. Sayer ◽

Patricio E. Cumsille

Keyword(s):

Growth Models ◽

Second Order ◽

Latent Growth ◽

Latent Growth Models

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Differential models and "differential structural equation modeling of intraindividual variability"

New methods for the analysis of change. ◽

10.1037/10409-001 ◽

2001 ◽

pp. 5-27 ◽

Cited By ~ 30

Author(s):

Steven M. Boker

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Intraindividual Variability ◽

Equation Modeling

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Multiple imputation with PAN.

New methods for the analysis of change. ◽

10.1037/10409-012 ◽

2001 ◽

pp. 357-377 ◽

Cited By ~ 32

Author(s):

Joseph L. Schafer

Keyword(s):

Multiple Imputation

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Toward a coherent framework for comparing trajectories of individual change.

New methods for the analysis of change. ◽

10.1037/10409-002 ◽

2001 ◽

pp. 35-64 ◽

Cited By ~ 43

Author(s):

Stephen W. Raudenbush

Keyword(s):

Individual Change

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Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class–latent growth modeling.

New methods for the analysis of change. ◽

10.1037/10409-010 ◽

2001 ◽

pp. 291-322 ◽

Cited By ~ 189

Author(s):

Bengt Muthén

Keyword(s):

Structural Equation Modeling ◽

Latent Variables ◽

Structural Equation ◽

Second Generation ◽

Latent Class ◽

Growth Modeling ◽

Latent Growth Modeling ◽

Equation Modeling ◽

Latent Growth

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Reliability for static and dynamic categorical latent variables: Developing measurement instruments based on a model of the growth process.

New methods for the analysis of change. ◽

10.1037/10409-009 ◽

2001 ◽

pp. 273-288 ◽

Cited By ~ 4

Author(s):

Linda M. Collins

Keyword(s):

Latent Variables ◽

Growth Process ◽

Measurement Instruments

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A structural equations modeling approach to the general linear mixed model.

New methods for the analysis of change. ◽

10.1037/10409-003 ◽

2001 ◽

pp. 67-98 ◽

Cited By ~ 14

Author(s):

Michael J. Rovine ◽

Peter C. M. Molenaar

Keyword(s):

Mixed Model ◽

Linear Mixed Model ◽

Structural Equations ◽

General Linear ◽

Structural Equations Modeling ◽

Modeling Approach ◽

General Linear Mixed Model

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Planned missing-data designs in analysis of change.

New methods for the analysis of change. ◽

10.1037/10409-011 ◽

2001 ◽

pp. 335-353 ◽

Cited By ~ 56

Author(s):

John W. Graham ◽

Bonnie J. Taylor ◽

Patricio E. Cumsille

Keyword(s):

Missing Data ◽

Planned Missing Data ◽

Analysis Of Change ◽

Planned Missing

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New methods for the analysis of change.Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By American Psychological Association

Trait–state models for longitudinal data.

The role of factorial invariance in modeling growth and change.

Second-order latent growth models.

Differential models and "differential structural equation modeling of intraindividual variability"

Multiple imputation with PAN.

Toward a coherent framework for comparing trajectories of individual change.

Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class–latent growth modeling.

Reliability for static and dynamic categorical latent variables: Developing measurement instruments based on a model of the growth process.

A structural equations modeling approach to the general linear mixed model.

Planned missing-data designs in analysis of change.

New methods for the analysis of change.
Latest Publications