An Effective Quantitative Randomized Response Survey Approach Employing Forced Answers

Abstract

Over the past few decades, survey researchers have become increasingly interested in the Over the past few decades, survey researchers have become increasingly interested in the randomized response technique. Numerous disciplines, including sociology, psychology, business, and education, have used the randomized response technique. Researchers can use it to address high non-response rates in sample surveys on delicate subjects such as monthly income, traffic infractions, income tax amount, and luxury spending. An optimal scrambling strategy that includes forced replies is presented in this research. The population mean estimator developed using the provided technique has been found to exhibit algebraic characteristics. The different model evaluation metrics were acquired and contrasted with existing models. The findings of this study indicate that the new quantitative method based on forced responses is more efficient than the current scrambling methods. Additionally, it combines model efficiency with a higher level of privacy, making it particularly valuable for practical applications. This paper also presents a helpful example of how this method can be utilized in sensitive sample surveys.