Interaction effects in growth modeling: A full model

In substantively important research, Li, Duncan, and Acock (2000) and Duncan, Duncan, Strycker, Li, and Alpert (1999) extended Jöreskog and Yang's (1996) structural equation model of latent interactions to latent growth modeling. We address 2 concerns with their approach: (a) Parameter constrai...

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Main Authors: Wen, Z, Marsh, H, Hau, K
Format: Journal article
Language:English
Published: 2002
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author Wen, Z
Marsh, H
Hau, K
author_facet Wen, Z
Marsh, H
Hau, K
author_sort Wen, Z
collection OXFORD
description In substantively important research, Li, Duncan, and Acock (2000) and Duncan, Duncan, Strycker, Li, and Alpert (1999) extended Jöreskog and Yang's (1996) structural equation model of latent interactions to latent growth modeling. We address 2 concerns with their approach: (a) Parameter constraints specified in their models were apparently inappropriate, and (b) they did not specify a full interaction model. Here we present more appropriate constraints and demonstrate a full interaction model for latent growth modeling that simultaneously estimates (a) the interaction between rates of change (slopes) of 2 predictors on the rate of change (slope) of the outcome and (b) the interaction between initial levels of growth (intercepts) of 2 predictors on the initial level (intercept) of outcome. Based on mathematical derivation and a comparison of alternative models fitted to simulated data, we show that our model is more appropriate and that their models can result in seriously biased parameter estimates. © 2002, Lawrence Erlbaum Associates, Inc.
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spelling oxford-uuid:649adce3-dc0a-4969-a8ca-d7ba775080d32022-03-26T18:19:56ZInteraction effects in growth modeling: A full modelJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:649adce3-dc0a-4969-a8ca-d7ba775080d3EnglishSymplectic Elements at Oxford2002Wen, ZMarsh, HHau, KIn substantively important research, Li, Duncan, and Acock (2000) and Duncan, Duncan, Strycker, Li, and Alpert (1999) extended Jöreskog and Yang's (1996) structural equation model of latent interactions to latent growth modeling. We address 2 concerns with their approach: (a) Parameter constraints specified in their models were apparently inappropriate, and (b) they did not specify a full interaction model. Here we present more appropriate constraints and demonstrate a full interaction model for latent growth modeling that simultaneously estimates (a) the interaction between rates of change (slopes) of 2 predictors on the rate of change (slope) of the outcome and (b) the interaction between initial levels of growth (intercepts) of 2 predictors on the initial level (intercept) of outcome. Based on mathematical derivation and a comparison of alternative models fitted to simulated data, we show that our model is more appropriate and that their models can result in seriously biased parameter estimates. © 2002, Lawrence Erlbaum Associates, Inc.
spellingShingle Wen, Z
Marsh, H
Hau, K
Interaction effects in growth modeling: A full model
title Interaction effects in growth modeling: A full model
title_full Interaction effects in growth modeling: A full model
title_fullStr Interaction effects in growth modeling: A full model
title_full_unstemmed Interaction effects in growth modeling: A full model
title_short Interaction effects in growth modeling: A full model
title_sort interaction effects in growth modeling a full model
work_keys_str_mv AT wenz interactioneffectsingrowthmodelingafullmodel
AT marshh interactioneffectsingrowthmodelingafullmodel
AT hauk interactioneffectsingrowthmodelingafullmodel