Local solutions in the estimation of growth mixture models.
University of North Carolina at Chapel Hill
Abstract
Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however, local solutions may still be problematic. Results from an empirical case study and a small Monte Carlo simulation show that failure to thoroughly consider the possible presence of local optima in the estimation of a growth mixture model can sometimes have serious consequences, possibly leading to adoption of an inferior solution that differs in substantively important…
Citation impact
- FWCI
- 18.18
- Percentile
- 100%
- References
- 47
Authors
2Topics & keywords
- Monte Carlo method
- Mixture model
- Maximum likelihood
- Econometrics
- Mathematical optimization
- Mathematics
- Local optimum
- Estimation theory