A useful approximation for planning block designs with potential missing data |
| |
Authors: | G. D. Herrin J. B. Neuhardt |
| |
Affiliation: | 1. The University of Michigan Ann Arbor , Michigan;2. Ohio State University Columbus , Ohio |
| |
Abstract: | Many empirical studies are planned with the prior knowledge that some of the data may be missed. This knowledge is seldom explicitly incorporated into the experiment design process for lack of a candid methodology. This paper proposes an index related to the expected determinant of the information matrix as a criterion for planning block designs. Due to the intractable nature of the expected determinantal criterion an analytic expression is presented only for a simple 2x2 layout. A first order Taylor series approximation function is suggested for larger layouts. Ranges over which this approximation is adequate are shown via Monte Carlo simulations. The robustness of information in the block design relative to the completely randomized design with missing data is discussed. |
| |
Keywords: | D-optimal expected determinant robust designs |
|