Estimation of Variance of the Regression Estimator.
Abstract
For estimating the variance of the regression estimator in simple random sampling without replacement, several design-based and model-based estimators and a new class of estimators are compared. Their second order expressions and biases are derived and compared. Empirical results on the biases and MSE's (Mean Squared Errors) of the variance estimators and the conditional and unconditional coverage probabilities of their associated t-intervals lend support to the theoretical results and suggest further questions. Originator-supplied keywords include: Variance estimator, Design-based, Model-based, Jack Knife (estimator), and Conditional coverage probabilities.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1984
- Accession Number
- ADA149407
Entities
People
- C. F. J. Wu
- L. Y. Deng
Organizations
- University of Wisconsin–Madison