ABSTRACT In this paper, we study the problem of heterogeneity in cervical mucus hydration at different times relative to the mucus peak both between cycles and women, specifying and estimating appropriate multilevel latent class models for longitudinal data. We estimate multilevel and growth latent class models which classify women on the basis of the evolution of cervical mucus characteristics observed over the fertile period of each menstrual cycle taking into account that we observe a different number of cycles per woman and correlation over time between consecutive observations. The effect of potential covariates on mucus evolution patterns is as well evaluated. Results confirm the existence of heterogeneity in mucus evolution between cycles and women. Moreover, an important significant effect of a woman’s age is found.

中文翻译：

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通过多级潜伏类方法评估月经周期中的异质性。

摘要在本文中，我们研究了相对于周期和女性之间的粘液峰值，不同时间宫颈粘液水化的异质性问题，为纵向数据指定并估计了适当的多级潜伏类模型。我们估计多水平和潜在增长类别模型，该模型根据每个月经周期的受精期观察到的宫颈粘液特征的演变对妇女进行分类，考虑到我们观察到的每个妇女的周期数不同，并且连续观察之间的时间相关性。还评估了潜在的协变量对粘液演变模式的影响。结果证实了周期与女性之间的粘液进化过程中存在异质性。此外，发现了女性年龄的重要显着影响。