Confidence Regions for Parameters of Linear Models
Andrew L. Rukhin
A method is suggested for constructing a conservative confidence region for the parameters of a general linear model. In meta-analytical applications, when the results of independent but heterogeneous studies are to be combined, this region can be employed with little to no knowledge of error variances. The required optimization problem is formulated and some properties of its solution are found.