Application of item sum technique for estimating quantitative sensitive mean on successive moves using auxiliary information

Estimation of sensitive issues is an adversely challenging task as it is highly influenced by social desirability bias leading to untrue response many times. Hence, the possible way out for these problems are randomized response technique or scrambled response technique or the item sum technique etc. The proposed work is a methodological advancement in estimation of quantitative sensitive mean in two move successive sampling by modifying the item sum technique. Detailed properties of new IST estimators have been discussed in general sampling design with applications in different sampling designs on successive moves. Theoretical considerations have been integrated with simulation studies to show the working version of modified IST on two move successive sampling.