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Population proportion

About: Population proportion is a research topic. Over the lifetime, 247 publications have been published within this topic receiving 4099 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper discusses the estimation of a population proportion in the presence of missing data and using auxiliary information at the estimation stage and indicates that the proposed optimal estimator gives desirable results in comparison to alternative estimators.

8 citations

Posted Content
01 Sep 2016-viXra
TL;DR: In this paper, the authors proposed some estimators for the population variance of the variable under study, which make use of information regarding the population proportion possessing a certain attribute, under simple random sampling without replacement (SRSWOR) scheme, up to the first order of approximation.
Abstract: This chapter proposes some estimators for the population variance of the variable under study, which make use of information regarding the population proportion possessing certain attribute. Under simple random sampling without replacement (SRSWOR) scheme, the mean squared error (MSE) up to the first order of approximation is derived. The results have been illustrated numerically by taking some empirical population considered in the literature.

8 citations

Journal ArticleDOI
TL;DR: In this paper, observations from inspection by a test method and a standard method are combined to provide estimators of population proportion, and of probabilities of misclassification for the test method, and some asymptotic properties of the resulting estimators are compared.
Abstract: : Observations from inspection by a 'test' method and a standard method are combined to provide estimators of population proportion, and of probabilities of misclassification for the test method. Results of Hochberg and Tenenbein and of Albers and Veldman are extended to the case where the standard method is not perfect, but its misclassification probabilities have known values. Both moment and maximum likelihood estimators are considered and some asymptotic properties of the resulting estimators are compared. (Author)

8 citations

Journal ArticleDOI
TL;DR: In this article, an estimator for population proportion p possessing sensitive attribute under unknown repeated trials model was proposed and the exact bias and mean square error of the proposed estimators were worked out.
Abstract: This paper proposes an estimator for population proportion p possessing sensitive attribute under unknown repeated trials model envisaged by Singh and Joarder (1997). The exact bias and mean square error of the proposed estimators are worked out. The superiority of the suggested estimator over Warner (1965) estimator and Singh and Joarder (1997) estimator have been discussed through numerical illustrations. An approximate expression for MSE is also given.

8 citations

Journal Article
TL;DR: In this article, a family of exponential ratio type estimators which uses the information regarding the population proportion possessing certain attribute was proposed and the expressions of bias and mean square error up to the first order approximations were derived.
Abstract: Grover and Kaur [4], Haq et al. [5], Abd-Elfattah et al. [1], Jhajj et al. [6], Shabbir and Gupta [8] and Koyuncu [7] have suggested some families of estimators by using the known population proportion of elements possessing attribute in the simple random sampling and in the two phase sampling. In this paper, after adapting these families of estimators to the stratified random sampling, we have proposed a family of exponential ratio type estimators which uses the information regarding the population proportion possessing certain attribute. For the proposed family of estimators, the expressions of bias and mean square error (MSE) up to the first order approximations are derived and the optimum case of the proposed family is discussed in theory. Also an empirical study is carried out to show its properties. Key words: Attribute, auxiliary information, efficiency, exponential ratio estimator, stratified random sampling.

7 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202112
202017
201914
201813
201713
201613