Detecting Appropriate Trajectories of Growth in Latent Growth Models: The Performance of Information-Based Criteria

@inproceedings{Whittaker2017DetectingAT,
  title={Detecting Appropriate Trajectories of Growth in Latent Growth Models: The Performance of Information-Based Criteria},
  author={Tiffany A. Whittaker and Jam Khojasteh},
  year={2017}
}
ABSTRACTLatent growth modeling (LGM) is a popular and flexible technique that may be used when data are collected across several different measurement occasions. Modeling the appropriate growth trajectory has important implications with respect to the accurate interpretation of parameter estimates of interest in a latent growth model that may impact educational policy decisions. A Monte Carlo simulation study was conducted to examine the accuracy of six information-based criteria (i.e., AIC… CONTINUE READING