A model that extends the Rasch model and the Partial Credit Model to account for subject-specific uncertainty when responding to items is proposed. It is demonstrated that ignoring the subject-specific uncertainty may yield biased estimates of model parameters. In the extended version of the model, uncertainty and the underlying trait are linked to explanatory variables. The parameterization allows to identify subgroups that differ in uncertainty and the underlying trait. The modeling approach is illustrated using data on the confidence of citizens in public institutions.

中文翻译：

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潜在特征模型的不确定性。

提出了一个模型，该模型扩展了 Rasch 模型和部分信用模型，以在响应项目时考虑特定主题的不确定性。事实证明，忽略特定主题的不确定性可能会产生对模型参数的有偏估计。在模型的扩展版本中，不确定性和潜在特征与解释变量相关联。参数化允许识别不确定性和潜在特征不同的子组。建模方法使用有关公民对公共机构的信心的数据进行说明。