Assessing the Effect of Nonresponse and Measurement Error Using a Novel Class of Efficient Estimators

Abstract

The purpose of any statistical analysis is to uncover the trend using real situations and provide an accurate model for future policies. In order to fulfill this aim, it is important to collect and use the data carefully and minimize the possibility of various types of errors. Nonresponse (NR) and measurement error (ME) are the two major types of nonsampling error that occur in almost every survey. We propose an estimator of the population mean and study its efficacy in the combined and separate effects of NR and ME. Some existing estimators are also considered for comparison. A simulation study was performed to see its efficiency numerically.