Using LISREL to Specify Unequal Level-Varying Structure for Complex Survey Data

• In Event: Poster Session 10
  In Poster Session: Multilevel Modeling: Complex Survey Data and Effect Size

Abstract

We provide an illustration of using LISREL for researchers to analyze complex survey data using CFA, Multilevel CFA, and Maximum Model techniques. Modeling multilevel structure of complex survey data is complicated because multilevel models are not an infallible statistical strategy unless the hypothesized model conforms to the real data structure. Methodologists have suggested to use different modeling techniques to investigate potential multilevel structure. With the provided LISREL syntax, researchers can set the higher- and lower-level factorial structure to fit MCFA, CFA and Maximum models. An empirical multilevel datasets were used to illustrate the usability and efficiency of our LISREL syntax on analyzing complex survey data. The analytic results were confirmed with Mplus to ensure the result consistency.

Authors

• Jiun-Yu Wu, National Chiao Tung University

• Jr-Hung Lin, National Chiao Tung University

• Yuan-Hsuan Lee, National Taichung University of Education