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Short Course: Introduction to Latent Variable Modeling
来源:  点击次数: 次 发布时间:2022-11-07   编辑:金沙以诚为本赢在信誉

Course outline

Thecourse introduces the core methods of latent variable modeling (LVM), including structural equation models (SEM) and Latent growth models (LGM), which uses in the structural equation modeling framework to estimate growth trajectories. These are a family of statistical approaches that explore complex relationships between and among latent (unobserved) and observed variables, as well as the longitudinal analysis technique to estimate growth over a period of time. The course will cover LVM with cross-sectional data in single and multiple-group settings and the methodology of LGM to investigate systematic change and growth and inter-individual variability in the change.

The course emphasizes the empirical applications of LVM and LGM techniques to broadly address relevant questions in the different disciplines. Course lectures, readings, and assignments will reflect this applied focus. At the end of the course, the student is expected to understand the essential issues within SEM and LGM. The students should be able to carry out analysis independently.

Lecturer

Fan Y. Wallentinis a Professor of Statistics at Uppsala University, Sweden. She received her Ph.D. in Statistics in 1997. She is a recipient of the Arnberg Prize from the Swedish Royal Academy of Sciences. Dr. Wallentin’s research program is on the theory and applications of latent variable modeling and other types of multivariate statistical analysis, particularly their applications in the social and behavioral sciences. She has published research articles in several leading statistics and psychometrics journals. She has taught courses related to latent variable modeling in Sweden, USA, China, and several European countries. She has broad experience in statistical consultation for researchers in social and behavioral sciences.

Prerequisites

This course suits students interested in analyzing the causal relationships among latent variables. The participants are expected to understand statistics, economics, and other social sciences with quantitative orientations. Students with their own research projects and data that can apply the methodology from the course are especially welcome.

Register the course

Please scan this QR code to register. Registration is open till Nov 11,12:00.

本课程受中央财经大学引智项目支持。

Schedule and contents

WeekOne

2022-11-12, 15.00 – 18.00

Measurement Theory

2022-11-13, 15.00 – 18.00

Measurement Models

2022-11-16, 15.00 – 17.00

Computer lab exercise

Week Two

2022-11-19, 15.00– 18.00

Structural equation models for cross-sectional data

2022-11-20, 15.00– 18.00

Structural equation models for multiple samples

2022-11-23, 15.00 – 17.00

Computer lab exercise

WeekThree

2022-11-26, 15.00– 18.00

Structural equation models for categorical data

2022-11-27, 15.00– 18.00

Latent variable models for longitudinal data

2022-11-27, 15.00– 17.00

Computer lab exercise

Week Four

2022-12-03, 15.00– 18.00

Latent growth curve models

2022-12-04, 15.00 – 18.00

Final computer exam

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