The Confounding Measure of Effects in Two-Level Regular Designs under Linear Model
In the design of experiments,the confounding of effects can cause the bias of parameter estimator in a linear model.This paper mainly proposes a confounding index for two-level regular designs to measure such bias.We introduce a new method to study the properties of the index and reveal the relationship between the confounding index,alias relation number,aliased component-number pattern,and word-length pattern.The confounding formula among lower-order effects is obtained to provide some conditions for optimal designs.Some examples are provided to illustrate the theoretical results.
万方数据
维普
