Calibrated Estimator for Sensitive Variables under Stratified Random Sampling
Keywords:
Auxiliary information, calibration, scrambled randomized response technique, stratified RR techniqueAbstract
Calibration sampling is a general tool to adjust the sampling weights and enhance the precision of the estimates. This technique is also helpful to reduce the non-response errors. In order to remove or minimize the biases produced by non-response errors and variances, the calibration technique is utilized. In this paper, Calibration technique is used to reduce the distance between the calibrated weights and the given distance measure. We propose new calibration estimators for estimating the population of a sensitive variable based on scrambled responses collected using some improved random response device and auxiliary information. This study is to propose some improved calibrated generalized estimators for estimation of population mean of a quantitative sensitive variable. The results show that the proposed estimator having an extra calibration constraint is more efficient.
References
Eichhorn BH, Hayre LS. Scrambled randomized response methods for obtaining sensitive quantitative data. J Stat Plan Inference. 1983; 7(4): 307-316.
Hansen MH, Hurwitz WN. The problem of non-response in sample surveys. J Am Stat Assoc. 1946; 41(236): 517-529.
Jabeen R, Sanaullah A, Hanif M, Zaka A. Two-exponential estimators for estimating population mean. Aims Math. 2021; 6(1): 737-753.
Kadilar C, Cingi H. Ratio estimators in stratified random sampling. Biometrical J. 2003; 45(2): 218-225.
Koyuncu N, Kadilar C. Calibration estimator using different distance measures in stratified random sampling. Int J Mod Eng Res. 2013; 3(1): 415-419.
Mangat NS, Singh R. An alternative randomized response procedure. Biometrika. 1990; 77(2): 439-442.
Mangat NS. An improved randomized response strategy. J R Stat Soc Series B Stat Methodol. 1994; 56(1): 93-95.
Pollock KH, Bek Y. A comparison of three randomized response models for quantitative data. J Am Stat Assoc. 1976; 71(356): 884-886.
Shabbir J, Gupta S. Improved ratio estimators in stratified sampling. AM J Math-S. 2005; 25(3-4): 293-311.
Tracy D, Singh S, Arnab R. Note on calibration in stratified and double sampling. Surv Meth. 2003; 29(1): 99-104.
Warner SL. Randomized response: A survey technique for eliminating evasive answer bias. J Am Stat Assoc. 1965; 60: 63-69.
Zaman T. Efficient estimators of population mean using auxiliary attribute in stratified random sampling. Adv Appl Stat. 2019; 56(2): 153-171.
Zaman T. An efficient exponential estimator of the mean under stratified random sampling. Math Pop Stud. 2021; 28(2): 104-121.
Zaman T, Bulut H. Modified regression estimators using robust regression methods and covariance matrices in stratified random sampling. Commun Stat-Theory Methods. 2020; 49(14): 3407-3420.
Zaman T, Kadilar C. On estimating the population mean using auxiliary character in stratified random sampling. J Stat Manag Syst. 2020; 23(8): 1415-1426.
Zaman T, Kadilar C. Exponential ratio and product type estimators of the mean in stratified two-phase sampling. AIMS Math. 2021; 6(5): 4265-4279.
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