We consider two-step estimation of latent variable models, in which just the measurement model is estimated in the first step and the measurement parameters are then fixed at their estimated values in the second step where the structural model is estimated. We show how this approach can be implemented for latent trait models (item response theory models) where the latent variables are continuous and their measurement indicators are categorical variables. The properties of two-step estimators are examined using simulation studies and applied examples. They perform well, and have attractive practical and conceptual properties compared to the alternative one-step and three-step approaches. These results are in line with previous findings for other families of latent variable models. This provides strong evidence that two-step estimation is a flexible and useful general method of estimation for different types of latent variable models.

翻译：我们考虑潜变量模型的两步估计方法，其中第一步仅估计测量模型，第二步将测量参数固定在其估计值上并估计结构模型。我们展示了如何将这种方法应用于潜特质模型（项目反应理论模型），其中潜变量为连续变量而其测量指标为分类变量。通过模拟研究和应用实例检验了两步估计量的性质。结果表明，相较于一步法和三步法，两步估计法表现良好，并具有吸引人的实践和概念特性。这些发现与先前对其他类型潜变量模型的研究结果一致。这为两步估计法作为适用于不同类型潜变量模型的灵活且实用的通用估计方法提供了有力证据。