Appropriate modelling of Likert‐type items should account for the scale level and the specific role of the neutral middle category, which is present in most Likert‐type items that are in common use. Powerful hierarchical models that account for both aspects are proposed. To avoid biased estimates, the models separate the neutral category when modelling the effects of explanatory variables on the outcome. The main model that is propagated uses binary response models as building blocks in a hierarchical way. It has the advantage that it can be easily extended to include response style effects and non‐linear smooth effects of explanatory variables. By simple transformation of the data, available software for binary response variables can be used to fit the model. The proposed hierarchical model can be used to investigate the effects of covariates on single Likert‐type items and also for the analysis of a combination of items. For both cases, estimation tools are provided. The usefulness of the approach is illustrated by applying the methodology to a large data set.

中文翻译：

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回归中的李克特量表和项目响应分析的层次模型

对Likert类型的项目进行适当的建模应考虑到规模级别和中性中间类别的特定作用，这在大多数常用的Likert类型的项目中都存在。提出了解决这两个方面的强大层次模型。为避免估计偏差，在对解释变量对结果的影响进行建模时，模型将中性类别分开。传播的主要模型以分层方式将二进制响应模型用作构建块。它的优点是可以很容易地扩展到包括解释变量的响应样式效果和非线性平滑效果。通过简单的数据转换，可以使用可用的二进制响应变量软件来拟合模型。提出的层次模型可用于研究协变量对单个李克特型物品的影响，也可用于物品组合的分析。对于这两种情况，都提供了估算工具。通过将该方法应用于大型数据集来说明该方法的有用性。