报告题目🦎：Instrumental Variables in Structural Equation Modelling with Ordinal Data

时间：2017年6月29日（星期四）14：00-15🛃：00

地点🥶：K8凯发南路校区学术会堂

报告人： Fan Y. Wallentin（扬帆）🫳🏽，瑞典乌普萨拉大学统计系 教授

摘要𓀅🐹：

Data collected from questionnaires are often in ordinal scale. Unweighted least squares (ULS), diagonally weighted least squares (DWLS) and normal-theory maximum likelihood (ML) are commonly used methods to fit structural equation models. Consistency of these estimators demands no structural misspecification. In this article, we conduct a simulation study to compare the equation-by-equation polychoric instrumental variable (PIV) estimation with ULS, DWLS, and ML. Accuracy of PIV for the correctly specified model and robustness of PIV for misspecified models are investigated through a confirmatory factor analysis (CFA) model and a structural equation model with ordinal indicators. The effects of sample size and nonnormality of the underlying continuous variables are also examined. The simulation results show that PIV produces robust factor loading estimates in the CFA model and in structural equation models. PIV also produces robust path coefficient estimates in the model where valid instruments are used. However, robustness highly depends on the validity of instruments.

Keywords: factor analysis, model misspecification, ordinal data, robustness

报告人简介🐹：

Fan Y. Wallentin是瑞典乌普萨拉大学统计系教授，也是统计系研究生项目主任和国际交流项目协调员🙎。Fan Y. Wallentin于1997年获得瑞典乌普萨拉大学统计学博士学位，并在该校任教。1998年🤦🏼‍♀️，获得 Scholarship for young female researcher🙍‍♂️，青年女性研究者奖学金由克努特与爱丽丝瓦伦堡基金会（瑞典）所颁发👮🏻‍♀️，为奖励女性研究者在统计与其他社会科学领域所作的贡献🍙。2000年获得Arnberg prize，安伯格奖是由瑞典皇家科K8凯发所颁发，为奖励在技术、经济与统计学领域中有杰出成果的学者而设立的🐃。该奖项每三年颁发一次，在奖项成立的100多年历史中，是该奖历史上第一位女性获奖人。研究兴趣集中在结构方程模型和其他类型的多元统计分析的理论和应用，是结构方程模型方面的权威专家。此外🤾🏽‍♀️，她在国际著名统计和心理学期刊发表了多篇相关领域的研究论文🧦，在社会和行为科学领域具有丰富的统计咨询经验。