Updated 12/20/2018
NG00062 - Episodic Memory Trajectories (EMTs) of 13,037 elderly

The Latent Class Mixed Model was used to assess the latent profiles of episodic memory trajectories (Proust-Lima et al. Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm. 2015). LCMM uses a mixed effects model with fixed and random effects terms to capture the characteristics of EM performance over-time. The fixed effect term considers all individuals from the entire study sample to estimate the EM parameters, including mean slope and mean intercept, which characterize the differences in over-time EM performance between individuals. 
On the other hand, the random effect term estimates the variance of the EM parameters, the intercepts and slopes around the fixed effect term for each study participant to model the differences in over-time EM performance within individuals.  LCMM fixed and random effects terms included total years of follow-up and years from baseline respectively as predictors of the latent class structure. LCMM estimation was performed using a maximum likelihood method and the optimal number of latent classes was empirically determined based on Bayesian information criterion.  When more than two clusters (EMTStables/EMTDecliners) were estimated, we reran LCCM analyses fixing the number of latent class to two for an easier interpretation of the results. 


The following subjects were dropped due to consent changes:
NACC114512
NACC337649
NACC488427
NACC627080
NACC994375

The following subjects were temoporarily removed while they are being reconsented:
NACC059686
NACC098472
NACC675928
NACC712454
NACC727243
NACC992352