This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 191
Type: Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #308112
Title: The Impact of Small Cluster Size on Multilevel Models: A Monte Carlo Examination of Two-Level Models with Binary and Continuous Predictors
Author(s): Bethany A. Bell*+ and Grant B. Morgan and Jeffrey D. Kromrey and John M. Ferron
Companies: University of South Carolina and University of South Carolina and University of South Florida and University of South Florida
Address: College of Education, Columbia, SC, 29208,
Keywords: multilevel modeling ; sample size ; binary predictors ; survey research
Abstract:

Recent methodological research has addressed the important issue of sample size at each level when estimating multilevel models. Although several design factors have been investigated in these studies, differences between continuous and binary predictor variables have not been scrutinized (previous findings are based on models with continuous predictor variables). To help address this gap in the literature, this Monte Carlo study focused on the consequences of level-2 sparseness on the estimation of fixed and random effects coefficients in terms of model convergence and both point and interval parameter estimates. The 5760 conditions simulated in the Monte Carlo study varied in terms of level-1 sample size, number of level-2 units, proportion of singletons (level-2 units with one observation), type of predictor, collinearity, intraclass correlation, and model complexity.


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