The results of Sample surveys play a vital role in decision making. One of the main issues being faced by survey statisticians during the collection of survey data is the problem of non-response which may affect survey cost and accuracy of estimates. The problem of non-response becomes more severe if the survey contains sensitive questions like related to family planning methods, use of drugs. To diminish the non-response rate arising in the case of direct questioning (DQ) technique, Warner (1965) proposed an indirect survey technique known as the randomized response (RR) technique. He addressed this problem for a cross-sectional data. This method is a well-known procedure that produces more valid responses on sensitive questions in surveys. The method avoids the direct link between respondent’s response and the sensitive question through the help of a randomization device. Thereby protecting respondent’s privacy which in turn greatly increases survey response rate. However, due to the complex nature of panel estimator, the work is missing the in the context of RR technique. To cover this gap, we propose a linear regression model in the context of panel surveys/longitudinal studies under the application of the RR technique. We solve all these issues through simulation study.