An Introduction to Latent Variable Growth Curve Modeling: by Terry E. Duncan

By Terry E. Duncan

This quantity offers Latent Variable development Curve Modeling for studying repeated measures. it's most probably that almost all readers have already mastered a lot of LGM's underpinnings, in up to repeated measures research of variance (ANOVA) versions are distinctive circumstances of LGMs that spotlight in basic terms at the issue ability. by contrast, an absolutely improved latent progress curve research takes under consideration either issue capability and variances. LGMs also are variations of the normal 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 e-book positive aspects significant themes--concepts and concerns, and applications--and is designed to exploit the reader's familiarity with ANOVA and conventional approaches in introducing LGM thoughts and offering useful examples.

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Extra info for An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications (Quantitative Methodology Series)

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628). 5 SPSS Specifications for the Sequelae of Change MANOVA MATRIX DATA VARIABLES=ROWTYPE_ ALC1 ALC2 ALC3 PROBBEH. BEGIN DATA. 000 END DATA. MANOVA ALC1 ALC2 ALC3 WITH PROBBEH /TRANSFORM(ALC1 ALC2 ALC3)=POLYNOMIAL /RENAME=CNST LIN QUAD PROBBEH /ANALYSIS=PROBBEH WITH CNST LIN QUAD /PRINT=CELLINFO(ALL) ERROR TRANSFORM PARAM(ALL) SIGNIF(MULTIV UNIV) /MATRIX=IN(*) /DESIGN=. 9 Regression Analysis for the Sequelae of Change MANOVA Dependent variable .. Problem Behavior COVARIATE CNST LIN QUAD B SE t Value Sig.

Equality of Covariance Matrices. The hypothesis that covariance matrices, (σ (γ)) i, are identical may be true even when the underlying model is unknown. 7. Equality of all Parameters in the Model. Although very restrictive, this hypothesis implies not only that both the first moments of the data, namely the means, as well as the second moments of the data about the means, namely the variances and covariances, are equal, but also that the LGM generating those matrices is identical in all respects across samples.

Each participant's level of alcohol consumption for the preceding 6 months was measured at three approximately equal intervals over a 2-year period. 1. 280 Note. Variances and covariances are in the triangle; means for the observed variables are presented in the bottom rows of the matrix. page_54 Page 55 Fig. 1. Representation of the multiple-sample LGM. The multiple-sample model tested is depicted in Fig. 1. 1. As can be seen in Fig. 1, the LGM includes a test of a linear trend in the data (loadings set at values of 0, 1, and 2 on the slope factor).

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