Muhammad Noor-ul-Amin

Generalized variance estimators in adaptive cluster sampling using single auxiliary variable

Abstract This study presents generalized variance estimators utilizing the information on single auxiliary variable in adaptive cluster sampling for finite population variance. The expressions for mean square errors and biases for proposed variance estimators are obtained. The result of simulation study presents that the suggested variance estimators for adaptive cluster sampling (ACS) design are most efficient for population variance as compare to Isaki (1983) variance estimator for SRSWOR.

Estimation of population mean for a sensitive variable in the presence of measurement error

Abstract Survey researchers are well aware that non-sampling errors are likely to occur if individuals are asked to reveal information about personal or socially undesirable behavior. Getting accurate responses to the so-called sensitive questions is an age-old problem in survey research. The idea of randomized response technique (RRT) was given by Warner (1965), to provide privacy to respondents in such surveys. In this paper, a generalized estimator of population mean for sensitive study variable is proposed. A simulation study is conducted to assess the performance of the proposed estimator in the presence and absence of measurement error.

Estimation of mean using generalized optional scrambled responses in the presence of non-sensitive auxiliary variable

Abstract In this article, the estimation of finite population mean of a sensitive variable based on generalized optional scrambled responses collected using a randomization device is presented under single sample approach. The estimator is then improved by using non-sensitive auxiliary information. Some special cases and privacy protection for proposed model has also been discussed. Simulation studies are conducted to evaluate the proposed device.

An EWMA control chart using two parametric ratio estimator

Abstract The control chart is one of the important industrial tools used for monitoring the manufacturing process. The performance of control chart may enhance when some additional information about variable under study is available. In this article, a new two parametric ratio estimator is introduced to design the exponentially weighted moving average control chart. The proposed control chart is more efficient than the existing control chart in detecting small and moderate shifts in the process mean at Phase II. The application of proposed control chart in the industry is given with the aid of a real example.

Estimation of population mean under systematic sampling

In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.

Estimation of population mean in systematic random sampling using auxiliary information

Abstract This paper provides a generalized ratio estimator for population mean in systematic random sampling. In this article we propose an estimator using single auxiliary variable X and having known population mean . We also tried to search out special cases out of generalized estimator using different combinations of constants. The mean square errors (MSEs) and mathematical conditions for efficiency of proposed estimators are derived. Numerical data are used to illustrate the mathematically derived MSEs and efficiency conditions. Efficiency of proposed estimators is proved as compared with classical ratio estimator.

Generalized estimator of population mean by using conventional and non-conventional measures in the presence of measurement errors

ABSTRACT In survey research, it is assumed that reported response by the individual is correct. However, given the issues of prestige bias, self-respect, respondents reported data often produces estimated values which are highly deviated from the true values. This causes measurement error (ME) to be present in the sample estimates. In this article, the estimation of population mean in the presence of measurement error using information on a single auxiliary variable is studied. A generalized estimator of population mean is proposed. The class of estimators is obtained by using some conventional and non-conventional measures. Simulation and numerical study is also conducted to assess the performance of estimators in the presence and absence of measurement error.