Evaluating the Power of Latent Growth Curve Models to Detect Individual Differences in Change

Evaluating the Power of Latent Growth Curve Models to Detect Individual Differences in Change

On the power of multivariate latent growth curve models to detect correlated change.

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris (1985) were used to evaluate the power to detect ...

Latent Growth Curve Models

The effect of multiple indicators on the power to detect inter-individual differences in change.

Hertzog et al. evaluated the statistical power of linear latent growth curve models (LGCMs) to detect individual differences in change, i.e., variances of latent slopes, as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We extend this work by investigating the effect of the number of indicators per measurement occasion on power. We analyti...

a synchronic and diachronic approach to the change route of address terms in the two recent centuries of persian language

terms of address as an important linguistics items provide valuable information about the interlocutors, their relationship and their circumstances. this study was done to investigate the change route of persian address terms in the two recent centuries including three historical periods of qajar, pahlavi and after the islamic revolution. data were extracted from a corpus consisting 24 novels w...