<p>The calibration techniques are used in survey sampling to get a precise estimate of the population parameter. In the present paper, we propose an efficient calibrated estimator of the stratified population mean using calibration technique in the simultaneous presence of measurement error and non-response, which has received limited attention in the existing literature. The information on a single auxiliary variable is utilized to envisage the calibrated estimator. The properties of the proposed calibrated estimator have been studied. The Taylor linearization technique has been used to derive the expression for the mean square error of the proposed calibrated estimator. An empirical study along with simulation analysis has also been accomplished to validate the efficiency of the proposed calibrated estimator. The study reveals that the proposed calibrated estimator outperforms over the estimators suggested by Hansen and Hurwitz (J Am Stat Assoc 41(236):517–529, 1946), Azeem and Hanif (Commun Stat-Theory Methods 46(4):1679–1693, 2017), Zahid and Shabbir (PLUS One 13(2):1–12, 2018) and Singh et al. (Rev Invest Oper 41(1):125–137, 2020). This work has contributed to extending calibration methodology to construct an estimator that performs effectively in the joint presence of measurement error and non-response.</p>