Master of Science (MSc)
Faculty of Science
With the presence of unequal sampling in a multilevel model, the weight inflated estimators for variance components can be biased even though the use of survey weights results in design consistent estimators of the parameters. In this thesis I will carry out a simulation study to examine the performance of current existing methods and I will examine the resampling method for correcting bias of estimators of variance components of a multilevel model with covariates. This study will be based on these three papers: “Weighting for Unequal Selection Probabilities in Multilevel Models” by D. Pfeffermann , C. J. Skinner, D.J. Holmes, H. Goldstein, and J. Rasbash (1998), Journal of the Royal Statistical Society Series B (Statistical Methodology), Vol. 60, No. 1, 23-40; “Design Consistent Estimators for a Mixed Linear Model on Survey Data” by Rong Huang and Mike Hidiroglou (2003), Business Survey Methods Division, Statistics Canada, Ottawa, Ontario K1Y 0A6; and “A resampling approach to estimate variance components of multilevel models” by Zilin Wang and Mary Thompson (2008), working paper.
Vakilian, Sara, "Simulation Studies on Estimation of Variance Components for Multilevel Models" (2009). Theses and Dissertations (Comprehensive). 922.