Developing new models for mulitmethod measurement of change and their application in the area of well-being research

在资助的第一阶段，开发了四种新的多方法纵向数据分析模型（LS-COM模型，LC-COM模型，LST-COM模型，LGC-COM模型）。模型已被定义的基础上的随机测量理论，这些模型的适用性进行了分析，通过几个模拟研究。下一阶段的目标是扩大这些模式的适用性，并以真实的数据说明其适用性。特别是，追求两个目标：1。将所有模型（LS-COM模型、LC-COM模型、LST-COM模型、LGC-COM模型）推广到具有有序响应类别的分类变量，并分析贝叶斯估计方法的适用性.将连续和分类响应变量的所有模型（LS-COM模型、LC-COM模型、LST-COM模型、LGC-COM模型）应用于真实的数据。应收集数据，分析依恋模式随时间和不同类型的关系的稳定性和特异性，并分析依恋和主观幸福感之间的相关性。

During the first period of funding four new models of multimethod longitudinal data analysis have been developed (LS-COM model, LC-COM model, LST-COM model, LGC-COM model). The models have been defined on the basis of stochastic measurement theory, and the applicability of these models have been analyzed by several simulation studies. The aim of the next period is to extend the applicability of these models and to illustrate their applicability by real data. In particular, two goals are pursued:1. Extension of all models (LS-COM model, LC-COM model, LST-COM model, LGC-COM model) to categorical variables with ordered response categories, and analysis of the applicability of Bayes estimation methods.2. Application of all models (LS-COM model, LC-COM model, LST-COM model, LGC-COM model) for continuous and categorical response variables to real data. The data should be collected to analyze the stability and specificity of attachment patterns over time and over different types of relationships, and to analyze correlations betwwen attachment and subjective well-being.