A parameter robust design for an immunoassay, such as the ELISA, is one that is not too sensitive to misspecification of the parameter values of the assumed regression model, and predicts a wide range of the unknown concentrations of a specified biochemical substance as precisely as possible. In this paper we use the ELISA example to demonstrate that the parameter robust optimality such as the weighted minimax and the expectation criteria have the potential of obtaining reasonably efficient parameter robust designs for immunoassays.
|Original language||English (US)|
|Number of pages||19|
|Journal||South African Statistical Journal|
|State||Published - Apr 24 2006|
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty