題目：長時數據分析的增長混合模型

主講：陳琦（美國北德州大學教育心理學副教授）

時間：1月5日上午10：00-12:00

地點：beat365体育官网南樓大報告廳

附一：報告英文摘要

Title：Growth Mixture Models (GMM) for Longitudinal Data Analysis（長時數據分析的增長混合模型）

Abstract: Growth Mixture Modeling (GMM) is a person-centered approach for analyzing longitudinal data. Using GMM, we can group individuals who are more similar to each other into categories. In this presentation, I will first introduce some concepts related to GMM, then present a simulation study examining the impact of ignoring a level of nesting structure in multilevel growth mixture models, and an empirical study applying GMM to investigate the differential effect of grade retention on the development of academic achievement from grade one to five on children retained in first grade over six years. Finally, I will briefly talk about the future directions of my research.