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.
| Original language | American English |
|---|---|
| Journal | Journal of Statistics and Management Systems |
| Volume | 20 |
| DOIs | |
| State | Published - Jan 1 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Disciplines
- Biostatistics
- Environmental Public Health
- Epidemiology
- Public Health
Keywords
- Regression estimators
- Stratified sampling schemes
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