Optimal Designs and Large Sample Tests for Linear Hypotheses.
Abstract
The study investigates the appropriateness of normal-theory inference for linear models having non-Gaussian errors. It is shown that bounds on the error of the Gaussian approximation depend on the design; the optimal designs are characterized and shown to be orthogonal. Bounds on the actual probabilities associated with Scheffe's projections, and with Dunnett's procedure for comparing several treatments with a control, are given in terms of their normal-theory approximations. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1973
- Accession Number
- AD0759733
Entities
People
- Donald R. Jensen
- Lawrence S. Mayer
- Raymond H. Myers
Organizations
- Virginia Tech