On estimation of population proportion in diagonal systematic sampling

Azeem, Muhammad Waqar

doi:10.1007/s41872-021-00165-0

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…The Subramani (2012) sampling design was further enhanced by a general systematic random sampling scheme by Subramani and Gupta (2014). Recently, Azeem (2021), Azeem (2022) and Khan, Azeem, Aftab, and Ismail (2022) studied various aspects of the estimation of parameters under different sample selection procedures.…”

Section: Introductionmentioning

confidence: 99%

A Novel Mixed Sampling Design Under the Existence of A Linear Trend

Azeem,

Khan

2024

Pak. J. Humanit. Soc. Sci

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In almost every field of social sciences, data is obtained from a small part drawn from a large population. Two common procedures to draw a sample from a population of interest are stratified random sampling and systematic random sampling. Each sampling procedure has been designed to be used in particular sample surveys. In real-world surveys, researchers may face a situation in which the simultaneous use of two or more sampling designs may be feasible to precisely estimate the population parameter rather than simply relying on a single sampling design. We propose a novel mixed-mode sampling scheme for real-world sample surveys in which the population units exhibit some sort of linear trend. Our proposed mixed sampling design combines the diagonal and linear systematic sampling with stratified random sampling. In real-world circumstances in which some sort of linear trend exists in the population units, we prove that our proposed mixed sampling design performs more efficiently than the available sampling designs. Additionally, unlike the systematic sampling design, the suggested sampling scheme can be applied practically for any sample and population size.

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Section: Introductionmentioning

confidence: 99%

A Novel Mixed Sampling Design Under the Existence of A Linear Trend

Azeem,

Khan

2024

Pak. J. Humanit. Soc. Sci

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Class of Calibrated Estimators of Population Proportion Under Diagonal Systematic Sampling Scheme

Audu,

Aphane,

Ahmad

et al. 2024

Mathematics

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Estimators of population characteristics which only exploit information of the study characters tend to be prone to outliers or extreme values that may characterize sampling information due to randomness in selection thereby making them to be less efficient and robust. One of the approaches often adopted in sampling surveys to address the aforementioned issue is to incorporate supplementary character information into the estimators through a calibration approach. Therefore, this study introduced two novel methods for estimating population proportion using diagonal systematic sampling with the help of an auxiliary variable. We developed two new calibration schemes and analyzed the theoretical properties (biases and mean squared errors) of the estimators up to the second-degree approximation. The theoretical findings were supported by simulation studies on five populations generated using the binomial distribution with various success probabilities. Biases, mean square errors (MSE) and the percentage relative efficiency (PRE) were computed, and the results revealed that the proposed estimators have the least biases, the least MSEs and higher PREs, indicating the superiority of the proposed estimators over the existing conventional estimator. The simulation results showed that our proposed estimators under the proposed calibration schemes performed more efficiently on average compared to the traditional unbiased estimator proposed for population proportion under diagonal systematic sampling. The superiority of the results of the proposed method over the conventional method in terms of bias, efficiency, efficiency gain, robustness and stability imply that the calibration approach developed in the study proved to be effective.

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On estimation of population proportion in diagonal systematic sampling

Cited by 2 publications

References 15 publications

A Novel Mixed Sampling Design Under the Existence of A Linear Trend

A Novel Mixed Sampling Design Under the Existence of A Linear Trend

Class of Calibrated Estimators of Population Proportion Under Diagonal Systematic Sampling Scheme

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