Generalised additive mixed models (GAMMs) are increasingly popular in dynamic speech analysis, where the focus is on measurements with temporal or spatial structure such as formant, pitch or tongue contours. GAMMs provide a range of tools for dealing with the non-linear contour shapes and complex hierarchical organisation characteristic of such data sets. This, however, means that analysts are faced with non-trivial choices, many of which have a serious impact on the statistical validity of their analyses. This paper presents type I and type II error simulations to help researchers make informed decisions about modelling strategies when using GAMMs to analyse phonetic data. The simulations are based on two real data sets containing F2 and pitch contours, and a simulated data set modelled after the F2 data. They reflect typical scenarios in dynamic speech analysis. The main emphasis is on (i) dealing with dependencies within contours and higher-level units using random structures and other tools, and (ii) strategies for significance testing using GAMMs. The paper concludes with a small set of recommendations for fitting GAMMs, and provides advice on diagnosing issues and tailoring GAMMs to specific data sets. It is also accompanied by a GitHub repository including a tutorial on running type I error simulations for existing data sets: https://github.com/soskuthy/gamm_strategies.

通用加法混合模型（GAMM）在动态语音分析中越来越流行，其中重点是对具有时间或空间结构（例如共振峰，音高或舌头轮廓）的测量。GAMM提供了一系列工具来处理此类数据集的非线性轮廓形状和复杂的层次组织特征。但是，这意味着分析师面临着非平凡的选择，其中许多选择都对其分析的统计有效性产生严重影响。本文介绍了I型和II型错误模拟，以帮助研究人员在使用GAMM分析语音数据时就建模策略做出明智的决策。模拟基于包含F2和音高轮廓的两个实际数据集，以及以F2数据为模型的模拟数据集。它们反映了动态语音分析中的典型场景。主要重点是（i）使用随机结构和其他工具处理轮廓和更高级别单位内的依存关系，以及（ii）使用GAMM进行重要性测试的策略。本文以一整套适合GAMM的建议作为结尾，并就诊断问题和针对特定数据集定制GAMM提供了建议。它还带有一个GitHub存储库，其中包括一个针对现有数据集运行I型错误模拟的教程：https：//github.com/soskuthy/gamm_strategies。本文以一整套适合GAMM的建议作为结尾，并就诊断问题和针对特定数据集定制GAMM提供了建议。它还带有一个GitHub存储库，其中包括一个针对现有数据集运行I型错误模拟的教程：https：//github.com/soskuthy/gamm_strategies。本文以一整套适合GAMM的建议作为结尾，并就诊断问题和针对特定数据集定制GAMM提供了建议。它还带有一个GitHub存储库，其中包括一个针对现有数据集运行I型错误模拟的教程：https：//github.com/soskuthy/gamm_strategies。