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|Author(s):||Andrew L. Rukhin;|
|Title:||Reducing Data Nonconformity in Linear Models|
|Published:||January 03, 2011|
|Abstract:||Stein phenomenon Summary Several procedures designed to reduce nonconformity in interlaboratory studies by shrinking data toward a consensus matrix weighted mean are suggested. Some of them are shown to have a smaller quadratic risk than the vector sample mean. Shrinkage toward a weighted means statistics appearing in random effects model. The results are illustrated by an example of collaborative studies.|
|Citation:||IMS Lecture Notes-Mongraph Series|
|Keywords:||Birge ratio, DerSimonian-Laird estimator, heteroscedasticity, key comparisons, meta-analysis, normal mean, reference value, shrinkage estimators|
|PDF version:||Click here to retrieve PDF version of paper (219KB)|