Handling Missing Data in Growth Mixture Models
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DOI: 10.3102/10769986221149140
Abstract: A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b)… read more here.
Keywords: growth mixture; missing data; handling missing; data growth ... See more keywords