Although there is a variety of statistical methods available for the analysis of longitudinal panel data, two approaches are of particular historical importance: the autoregressive (simplex) model and the latent trajectory (curve) model. Curran and Bollen (2004) have introduced Autoregressive Latent Trajectories (ALT) that integrate a standard growth curve with autoregressive relationships between the observed variables. The present paper discusses, via a simulation study, the properties of this approach, with the aim of deriving the relationship between nonlinearity and nonstationary in latent growth models.
Bianconcini S., Mignani S. (2009). Relating nonlinearity to nonstationarity in latent growth models. ST. PETERSBURG : s.n.
Relating nonlinearity to nonstationarity in latent growth models
BIANCONCINI, SILVIA;MIGNANI, STEFANIA
2009
Abstract
Although there is a variety of statistical methods available for the analysis of longitudinal panel data, two approaches are of particular historical importance: the autoregressive (simplex) model and the latent trajectory (curve) model. Curran and Bollen (2004) have introduced Autoregressive Latent Trajectories (ALT) that integrate a standard growth curve with autoregressive relationships between the observed variables. The present paper discusses, via a simulation study, the properties of this approach, with the aim of deriving the relationship between nonlinearity and nonstationary in latent growth models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.