This peer commentary emphasizes the importance of implementing more sophisticated analytical techniques in infant research. It provides examples of information extracted from classical paradigms, the habituation–dishabituation paradigm, the visual pair preference task and the visual expectation paradigm, by means of models such as a latent variables mixture model. Although modelling techniques have been implemented in infant research for many years, they have always been a marginal phenomenon because infant data were mainly analysed using mean level comparisons. This commentary outlines the principal advantage of modelling infant behavioural data: there is no other way to obtain information on behaviour and its development at the individual infant level than through a model, and models can be adapted to the specific requirements of an experimental setting's data. However, there are expenses to such techniques: it takes time both to build and to understand a model for a specific experimental setting, and both data and code need to be made available (and thus readable, i.e. following certain style requirements). If as a field, we do not refrain from investing such time, modelling approaches can be a very useful tool for a more reliable infant research.

中文翻译：

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婴儿研究中的建模过程

该同行评论强调了在婴儿研究中实施更复杂的分析技术的重要性。它通过潜变量混合模型等模型提供了从经典范式、习惯化-去习惯化范式、视觉对偏好任务和视觉期望范式中提取的信息示例。尽管建模技术已在婴儿研究中实施多年，但它们一直是一种边缘现象，因为婴儿数据主要使用平均水平比较进行分析。本评论概述了对婴儿行为数据建模的主要优势：除了通过模型之外，没有其他方法可以获取有关个体婴儿水平的行为及其发展的信息，模型可以适应实验设置数据的特定要求。然而，这些技术是有代价的：建立和理解特定实验设置的模型都需要时间，并且数据和代码都需要可用（因此是可读的，即遵循某些样式要求）。如果作为一个领域，我们不克制投入这样的时间，那么建模方法可以成为更可靠的婴儿研究的非常有用的工具。