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Determining the Number of Latent Classes in Single-and Multiphase Growth Mixture Models

机译：确定单相和多相生长混合物模型中潜在类别的数量

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摘要

Stage-sequential (or multiphase) growth mixture models are useful for delineating potentially different growth processes across multiple phases over time and for determining whether latent subgroups exist within a population. These models are increasingly important as social behavioral scientists are interested in better understanding change processes across distinctively different phases, such as before and after an intervention. One of the less understood issues related to the use of growth mixture models is how to decide on the optimal number of latent classes. The performance of several traditionally used information criteria for determining the number of classes is examined through a Monte Carlo simulation study in single- and multiphase growth mixture models. For thorough examination, the simulation was carried out in 2 perspectives: the models and the factors. The simulation in terms of the models was carried out to see the overall performance of the information criteria within and across the models, whereas the simulation in terms of the factors was carried out to see the effect of each simulation factor on the performance of the information criteria holding the other factors constant. The findings not only support that sample size adjusted Bayesian Information Criterion would be a good choice under more realistic conditions, such as low class separation, smaller sample size, or missing data, but also increase understanding of the performance of information criteria in single- and multiphase growth mixture models.
机译：阶段顺序（或多阶段）生长混合物模型可用于描述随着时间的推移在多个阶段中可能不同的生长过程，并用于确定种群中是否存在潜在的亚群。随着社会行为科学家对更好地理解不同阶段（例如干预前后）的变化过程感兴趣，这些模型变得越来越重要。与使用增长混合模型有关的鲜为人知的问题之一是如何确定潜在类别的最佳数量。通过在单相和多相生长混合物模型中进行的蒙特卡洛模拟研究，研究了几种用于确定类别数量的传统信息标准的性能。为了进行全面检查，仿真从两个角度进行：模型和因素。进行了模型方面的模拟，以查看模型内和模型之间信息标准的整体性能，而进行因素方面的模拟，以查看每个模拟因素对信息性能的影响。保持其他因素不变的标准。这些发现不仅支持在更现实的条件下（例如低分类分离，较小的样本量或缺少数据），调整样本量的贝叶斯信息准则将是一个不错的选择，而且还增加了对单一样本和样本样本中信息标准性能的理解。多相生长混合物模型。

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