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- https://doi.org/10.1080/09720510.2017.1411027
On regression estimators for different stratified sampling schemes
- Nov 2, 2017
- Journal of Statistics and Management Systems
- Arpita Chatterjee +5 more
Abstract
Two types of stratified regression estimators for the population mean, the separate and the combined estimators, are investigated using stratified random sampling scheme (SSRS) and stratified ranked set sampling (SRSS). We derived mean and variance of the proposed estimators. In addition, we compared the performance of the regression estimators using SRSS with respect to SSRS by simulation. Our derivations and simulations revealed that our proposed estimators are unbiased and using SRSS is more efficient than using SSRS. The procedure are illustrated by using the bilirubin levels in babies in a neonatal intensive care unit data.
- # Stratified Ranked Set Sampling
- # Stratified Random Sampling Scheme
- # Levels In Babies
- # Regression Estimators
- # Bilirubin Levels
- # Stratified Sampling Scheme
- # Stratified Sampling
- # Stratified Set
- # Stratified Estimators
- # Neonatal Data