The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM)
The concept of change over time is fundamental to many phenomena investigated in organizational research. This didactically oriented article proposes an integrative approach incorporating longitudinal mean and covariance structures analysis and multiple indicator latent growth modeling to aid organi...
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1998
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sg-smu-ink.soss_research-12222010-08-31T09:30:04Z The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) CHAN, David The concept of change over time is fundamental to many phenomena investigated in organizational research. This didactically oriented article proposes an integrative approach incorporating longitudinal mean and covariance structures analysis and multiple indicator latent growth modeling to aid organizational researchers in directly addressing fundamental questions concerning the conceptualization and analysis of change over time. The approach is illustrated using a numerical example involving several organizationally relevant variables. Advantages, limitations, and extensions of the approach are discussed. 1998-10-01T07:00:00Z text https://ink.library.smu.edu.sg/soss_research/223 info:doi/10.1177/109442819814004 Research Collection School of Social Sciences eng Institutional Knowledge at Singapore Management University Industrial and Organizational Psychology Quantitative Psychology |
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Industrial and Organizational Psychology Quantitative Psychology CHAN, David The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
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The concept of change over time is fundamental to many phenomena investigated in organizational research. This didactically oriented article proposes an integrative approach incorporating longitudinal mean and covariance structures analysis and multiple indicator latent growth modeling to aid organizational researchers in directly addressing fundamental questions concerning the conceptualization and analysis of change over time. The approach is illustrated using a numerical example involving several organizationally relevant variables. Advantages, limitations, and extensions of the approach are discussed. |
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CHAN, David |
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CHAN, David |
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CHAN, David |
title |
The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
title_short |
The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
title_full |
The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
title_fullStr |
The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
title_full_unstemmed |
The Conceptualization and Analysis of change over Time: An Integrative Approach Incorporating Longitudinal Means and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) |
title_sort |
conceptualization and analysis of change over time: an integrative approach incorporating longitudinal means and covariance structures analysis (lmacs) and multiple indicator latent growth modeling (mlgm) |
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Institutional Knowledge at Singapore Management University |
publishDate |
1998 |
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https://ink.library.smu.edu.sg/soss_research/223 |
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1770568014191656960 |