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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.


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Journal ArticleDOI
TL;DR: In this article, improved classes of estimators have been proposed for estimating the population means of the study character using the information on auxiliary character and attribute in the presence of non-response on study character only and their properties are studied.
Abstract: In this paper, improved classes of estimators have been proposed for estimating the population means of the study character using the information on auxiliary character and attribute in the presence of non-response on study character only and their properties are studied. The conditions for attaining the minimum mean square error of the proposed classes of estimators are also given. Further, the problem has been extended to the two phase sampling when the population proportion and mean of auxiliary character are not known. Two wider classes of generalized estimators under these conditions have been proposed and their properties are studied. The expressions of optimum sample size for first phase, second phase and sub-sampling fraction have been obtained in case of fixed cost as well as for fixed precision. Theoretical and empirical studies have been made with relevant estimators to show the efficiency of the proposed classes of estimators with real data set from census handbook published by Government of India.

7 citations

Journal ArticleDOI
TL;DR: The described approach to estimating the achievable benefit of cancer therapy is robust to model uncertainties, rapidly adaptable and is transparent, however, estimates rely on the quality of model data sources and may be affected by model assumptions.

7 citations

Journal ArticleDOI
TL;DR: A hierarchical Bayesian model is presented in which the firststage binary responses have independent Bernoulli distributions, and each subsequent stage is modeled using a beta distribution, which is parameterized by its mean and a correlation coefficient to infer the finite population proportion of each area.
Abstract: We extend the twofold small-area model of Stukel and Rao (1997; 1999) to accommodate binary data. An example is the Third International Mathematics and Science Study (TIMSS), in which pass-fail data for mathematics of students from US schools (clusters) are available at the third grade by regions and communities (small areas). We compare the finite population proportions of these small areas. We present a hierarchical Bayesian model in which the firststage binary responses have independent Bernoulli distributions, and each subsequent stage is modeled using a beta distribution, which is parameterized by its mean and a correlation coefficient. This twofold small-area model has an intracluster correlation at the first stage and an intercluster correlation at the second stage. The final-stage mean and all correlations are assumed to be noninformative independent random variables. We show how to infer the finite population proportion of each area. We have applied our models to synthetic TIMSS data to show that the twofold model is preferred over a onefold small-area model that ignores the clustering within areas. We further compare these models using a simulation study, which shows that the intracluster correlation is particularly important.

7 citations

Journal ArticleDOI
TL;DR: Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the Rapid Assessment Tools Package, a locally designed and deployed tool, may provide populationbased estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts.
Abstract: INTRODUCTION: Local health departments are among the first agencies to respond to disasters or other mass emergencies. However, they often lack the ability to handle large-scale events. Plans including locally developed and deployed tools may enhance local response. Simplified cluster sampling methods can be useful in assessing community needs after a sudden-onset, short duration event. METHODS: Using an adaptation of the methodology used by the World Health Organization Expanded Programme on Immunization (EPI), a Microsoft Access-based application for two-stage cluster sampling of residential addresses in Louisville/Jefferson County Metro, Kentucky was developed. The sampling frame was derived from geographically referenced data on residential addresses and political districts available through the Louisville/Jefferson County Information Consortium (LOJIC). The program randomly selected 30 clusters, defined as election precincts, from within the area of interest, and then, randomly selected 10 residential addresses from each cluster. The program, called the Rapid Assessment Tools Package (RATP), was tested in terms of accuracy and precision using data on a dichotomous characteristic of residential addresses available from the local tax assessor database. A series of 30 samples were produced and analyzed with respect to their precision and accuracy in estimating the prevalence of the study attribute. Point estimates with 95% confidence intervals were calculated by determining the proportion of the study attribute values in each of the samples and compared with the population proportion. To estimate the design effect, corresponding simple random samples of 300 addresses were taken after each of the 30 cluster samples. RESULTS: The sample proportion fell within +/-10 absolute percentage points of the true proportion in 80% of the samples. In 93.3% of the samples, the point estimate fell within +/-12.5%, and 96.7% fell within +/-15%. All of the point estimates fell within +/-20% of the true proportion. Estimates of the design effect ranged from 0.926 to 1.436 (mean = 1.157, median = 1.170) for the 30 samples. CONCLUSIONS: Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the RATP, a locally designed and deployed tool, may provide population-based estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts. Language: en

7 citations

Journal ArticleDOI
TL;DR: A novel sampling algorithm, referred to as algorithm PAS (standing for proportion approximation sampling), is explored, which can stably provide high-quality samples with corresponding computational overhead, whereas algorithm EQAS can flexibly generate samples with the desired balance between sampling quality and sampling efficiency.
Abstract: We explore in this paper a novel sampling algorithm, referred to as algorithm PAS (standing for proportion approximation sampling), to generate a high-quality online sample with the desired sample rate. The sampling quality refers to the consistency between the population proportion and the sample proportion of each categorical value in the database. Note that the state-of-the-art sampling algorithm to preserve the sampling quality has to examine the population proportion of each categorical value in a pilot sample a priori and is thus not applicable to incremental mining applications. To remedy this, algorithm PAS adaptively determines the inclusion probability of each incoming tuple in such a way that the sampling quality can be sequential/preserved while also guaranteeing the sample rate close to the user specified one. Importantly, PAS not only guarantees the proportion consistency of each categorical value but also excellently preserves the proportion consistency of multivariate statistics, which will be significantly beneficial to various data mining applications. For better execution efficiency, we further devise an algorithm, called algorithm EQAS (standing for efficient quality-aware sampling), which integrates PAS and random sampling to provide the flexibility of striking a compromise between the sampling quality and the sampling efficiency. As validated in experimental results on real and synthetic data, algorithm PAS can stably provide high-quality samples with corresponding computational overhead, whereas algorithm EQAS can flexibly generate samples with the desired balance between sampling quality and sampling efficiency

7 citations


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