Prior Distributions for Variance Parameters in Multiple Membership Multilevel Modeling

• In Event: Poster Session 9
  In Poster Session: Using Multilevel Modeling in Substantive Research

Abstract

This simulation study examines how the selection of priors within a Bayesian framework affects variance parameter estimates in multiple membership multilevel modeling. Two prior distributions were used to assess the impact on parameter estimates: gamma and uniform distributions. Substantial over-estimation of the level two variance component was identified for both gamma and uniform distributions. With a larger number of level two units, however, the differences of parameter estimates gamma and uniform priors were diminished. Increasing level one sample size has relatively little impact on the level two variance component parameter estimates for both prior distributions. The results suggest that researchers should be cautious in selecting accurate priors especially with a relatively small number of level two units.

Authors

• Hyewon Chung, Chungnam National University

• Jiseon Kim, University of Washington - Seattle

• Ryoungsun Park, Wayne State University

• Hyeonjeong Jeon, Chungnam National University