Analyzing Complex Longitudinal Data in Educational Research: A Demonstration With Project English Language and Literacy Acquisition Data Using xxM

• In Event: Analyzing Longitudinal Data in Multilevel Modeling and Latent Growth Modeling

Abstract

When analyzing complex longitudinal data especially those from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients) while ignore the equally important random part (i.e., the random effect variances) of the model. By using the Project ELLA data, we demonstrated the importance of adequately taking the complex data structure into account by carefully specifying the random part of the model—not only it can affect the variance estimates but also it can offer different perspectives of the data such as information related to the developmental process. We have used xxM (Mehta, 2013) which can flexibly estimate different grade level variances and the potential carry-over effect from each grade factor to the later time measures.

Authors

• Oiman Kwok, Texas A&M University - College Station

• Hok Chio (Mark) Lai, University of Southern California

• Fuhui Tong, Texas A&M University - College Station

• Rafael Lara-Alecio, Texas A&M University

• Beverly J. Irby, Texas A&M University - College Station

• Myeongsun Yoon, Texas A&M University

• Yu-Chen Yeh, Texas A&M University - College Station