Longitudinal data analysis using structural equation models.
Latest Publications

TOTAL DOCUMENTS

(FIVE YEARS 0)

H-INDEX

(FIVE YEARS 0)

Published By American Psychological Association

1433817152, 1433817160, 9781433817151, 9781433817168

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Coda: The future is yours!

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-036 ◽

2014 ◽

pp. 367-372

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

The Future

Download Full-text

Factor invariance in longitudinal research.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-033 ◽

2014 ◽

pp. 345-350

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Longitudinal Research ◽

Factor Invariance

Download Full-text

The popular repeated measures analysis of variance.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-031 ◽

2014 ◽

pp. 329-330

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Analysis Of Variance ◽

Repeated Measures ◽

Repeated Measures Analysis

Download Full-text

Applying a bivariate change model with multiple groups.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-029 ◽

2014 ◽

pp. 319-321

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Change Model ◽

Multiple Groups

Download Full-text

Dynamic processes over groups.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-027 ◽

2014 ◽

pp. 307-314

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Dynamic Processes

Download Full-text

Plotting bivariate latent change score results.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-026 ◽

2014 ◽

pp. 301-304

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Change Score ◽

Latent Change Score

Download Full-text

Analyses based on cross-lagged regression and changes.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-022 ◽

2014 ◽

pp. 255-269

Author(s):

John J. McArdle ◽

John R. Nesselroade

Download Full-text

Alternative common factors with multiple longitudinal observations.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-019 ◽

2014 ◽

pp. 221-229

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Common Factors

Download Full-text

Considering factorial invariance in longitudinal structural equation modeling.

Longitudinal data analysis using structural equation models. ◽

10.1037/14440-018 ◽

2014 ◽

pp. 207-219

Author(s):

John J. McArdle ◽

John R. Nesselroade

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Factorial Invariance ◽

Equation Modeling ◽

Longitudinal Structural Equation Modeling

Download Full-text

Longitudinal data analysis using structural equation models.
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By American Psychological Association

Coda: The future is yours!

Factor invariance in longitudinal research.

The popular repeated measures analysis of variance.

Applying a bivariate change model with multiple groups.

Dynamic processes over groups.

Plotting bivariate latent change score results.

Analyses based on cross-lagged regression and changes.

More alternative factorial solutions for longitudinal data.

Alternative common factors with multiple longitudinal observations.

Considering factorial invariance in longitudinal structural equation modeling.

Export Citation Format

Longitudinal data analysis using structural equation models.Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By American Psychological Association

Coda: The future is yours!

Factor invariance in longitudinal research.

The popular repeated measures analysis of variance.

Applying a bivariate change model with multiple groups.

Dynamic processes over groups.

Plotting bivariate latent change score results.

Analyses based on cross-lagged regression and changes.

More alternative factorial solutions for longitudinal data.

Alternative common factors with multiple longitudinal observations.

Considering factorial invariance in longitudinal structural equation modeling.

Longitudinal data analysis using structural equation models.
Latest Publications