IMPUTATION USING REGRESSION ESTIMATORS FOR ESTIMATING POPULATION MEAN IN TWO-PHASE SAMPLING

  • Narendra Singh Thakur Centre for Mathematical Sciences (CMS), Banasthali University, Rajasthan, India, Pin-304022
  • Kalpana Yadav Centre for Mathematical Sciences (CMS), Banasthali University, Rajasthan, India, Pin-304022
  • Sharad Pathak Department of Mathematics and Statistics, Dr. H. S. Gour Central University, Sagar (M.P.), India, Pin-470003
Keywords: Estimation, Missing data, Regression estimators, Bias, Mean squared error (MSE), Two-phase sampling, SRSWOR, Large sample approximations

Abstract

This paper presents the estimation of mean in presence of missing data under two-phase sampling design using regression estimators as a tool for imputation while the size of responding ( ) 1 R and non-responding ( ) 2 R group is considered as a random variable. The bias and mean squared error of suggested estimators are derived in the form of population parameters using the concept of large sample approximation. Numerical study is performed over two populations by using the expressions of bias and mean squared error and efficiency compared with existing estimators.

 

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Published
2012-05-10
Section
Articles