Stein-rule estimation in genetic carrier testing

Tong Zeng and Carter Hill

International Journal of Computational Economics and Econometrics, 2020, vol. 10, issue 2, 111-128

Abstract: In this paper, we apply the fully correlated random parameters logit (FCRPL) model to the genetic carrier testing data using shrinkage estimation. We show that shrinkage estimates with higher shrinkage constant improve the percentages of correct predicted choices by 2% and 10% respectively with Jewish and general population samples. The mean estimates of elasticity based on the shrinkage estimates are closer to those with the FCRPL model estimates and have smaller standard errors than the corresponding results based on the uncorrelated random parameters logit model estimates.

Keywords: pretest estimator; positive-part Stein-like estimator; likelihood ratio test; random parameters logit model. (search for similar items in EconPapers)
Date: 2020
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