Stratified Extreme Ranked Set Sample With Application To Ratio Estimators

Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method