This paper considers the classical and inverse calibration estimators and discusses the consequences of departure from normality of errors on their bias and mean squared error properties when the errors in calibration process are small.

BACKGROUND Cross-sectional surveys utilizing biomarkers that test for recent infection provide a convenient and cost effective way to estimate HIV incidence. In particular, the BED assay has been developed for this purpose. Controversy surrounding the way in which false positive results from the biomarker should be handled has lead to a number of different estimators that account for imperfect ...

The estimation of average treatment effects based on observational data is extremely important in practice and has been studied by generations of statisticians under different frameworks. Existing globally efficient estimators require non-parametric estimation of a propensity score function, an outcome regression function or both, but their performance can be poor in practical sample sizes. Wit...

Variance is one of the most important measures descriptive statistics and commonly used for statistical analysis. The traditional second-order central moment based variance estimation a widely utilized methodology. However, estimator highly affected in presence extreme values. So this paper initially, proposes two classes calibration estimators on an adaptation recently proposed by Koyuncu then...

Using auxiliary information, the calibration approach modifies original design weights to enhance mean estimates. This paper initially proposes two families of estimators based on an adaptation presented by recent researchers, and then, it presents a new family with set some constraints under stratified median ranked sampling (MRSS). The result has also been implemented situation two-stage To b...