Abstract
Multitiered experiments are characterized by involving multiple randomizations, in a sense that we make explicit. We compare and contrast six types of multiple randomizations, using a wide range of examples, and discuss their use in designing experiments. We outline a system of describing the randomizations in terms of sets of objects, their associated tiers and the factor nesting, using randomization diagrams, which give a convenient and readily assimilated summary of an experiment's randomization. We also indicate how to formulate a randomization-based mixed model for the analysis of data from such experiments.
Original language | English |
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Pages (from-to) | 571-599 |
Number of pages | 29 |
Journal | Journal of the Royal Statistical Society: Series B (Statistical Methodolgy) |
Volume | 68 |
Issue number | 4 |
Publication status | Published - 2006 |
Keywords
- design of experiments
- mixed models
- multiple randomizations
- multitiered experiments
- pseudofactors
- radnomization
- superimposed experiments
- tiers
- two-phase experiments