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Bootstrapping data with multiple levels of variation |
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| Authors: | Christopher A. Field Zhen Pang Alan H. Welsh |
| Affiliation: | 1. Department of Mathematics and Statistics Dalhousie University, Halifax, Nova Scotia Canada B3H 3J5;2. Division of Mathematical Sciences Nanyang Technological University, Singapore 637371;3. Centre for Mathematics and its Applications The Australian National University, Canberra Australia, ACT 0200 |
| Abstract: | The authors consider general estimators for the mean and variance parameters in the random effect model and in the transformation model for data with multiple levels of variation. They show that these estimators have different distributions under the two models unless all the variables have Gaussian distributions. They investigate the asymptotic properties of bootstrap procedures designed for the two models. They also report simulation results and illustrate the bootstraps using data on red spruce trees. |
| Keywords: | Best linear unbiased prediction hierarchical data mixed model quasi‐likelihood estimation random effect unbalanced data |