By Terry E. Duncan
This quantity offers Latent Variable progress Curve Modeling for reading repeated measures. it truly is most likely that the majority readers have already mastered a lot of LGM's underpinnings, in up to repeated measures research of variance (ANOVA) versions are specific circumstances of LGMs that attention purely at the issue potential. by contrast, an absolutely elevated latent development curve research takes under consideration either issue skill and variances. LGMs also are versions of the traditional linear structural version. as well as utilizing regression coefficients and variances and covariances of the autonomous variables, they contain a median constitution into the version. The publication good points significant themes--concepts and matters, and applications--and is designed to exploit the reader's familiarity with ANOVA and conventional systems in introducing LGM strategies and providing sensible examples.
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Additional info for An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications (Quantitative Methodology Series)
Representation of the added growth LGM. page_58 Page 59 Here, an additional growth factor is introduced for one population. Muthén and Curran call this the added growth factor. , intercept and slope) are the same in both groups, the added growth factor, specified in one group, represents incremental/decremental growth that is specific to that group. As can be seen in Fig. 2, the added growth factor is specified to capture linear differences between the two groups. In this case, the linear slope factor captures normative growth that is common to both groups.
Note that all other parameters remained constrained across the two groups. An examination of the univariate LM statistics for the respecified model revealed that none of the remaining constraints, if released, would significantly improve overall model fit. 2 Alternative Multiple-Sample Analysis of ''Added Growth" LGM As in conventional multiple-population latent variable analyses, the preceding analyses specified a two-factor growth model in both groups, testing for equality of parameters across the two populations.
1. Representation of the combined cohort-sequential-true longitudinal LGM. model is assumed in each cohort, allowing for tests of hypotheses concerning convergence across separate groups and the feasibility of specifying a common growth trajectory over the 6 years represented by the design. The cohort-sequential model serves as a proxy for the true longitudinal model, which uses data from yearly assessments of the 11-year-old cohort (Group 4) over a 5year period beginning at 12 years of age. 1.
An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications (Quantitative Methodology Series) by Terry E. Duncan