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Relevant bibliographies by topics / Stage sampling Design

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Journal articles

Academic literature on the topic 'Stage sampling Design'

Author: Grafiati

Published: 8 September 2023

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Journal articles on the topic "Stage sampling Design"

1

Skinner, C. J. "Design Effects of Two-Stage Sampling." Journal of the Royal Statistical Society: Series B (Methodological) 48, no. 1 (1986): 89–99. http://dx.doi.org/10.1111/j.2517-6161.1986.tb01393.x.

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2

Ugwu, Michael C., and Mbanefo S. Madukaife. "Two-stage cluster sampling with unequal probability sampling in the first stage and ranked set sampling in the second stage." Statistics in Transition New Series 23, no. 3 (2022): 199–214. http://dx.doi.org/10.2478/stattrans-2022-0038.

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Abstract In this research work we introduce a new sampling design, namely a two-stage cluster sampling, where probability proportional to size with replacement is used in the first stage unit and ranked set sampling in the second in order to address the issue of marked variability in the sizes of population units concerned with first stage sampling. We obtained an unbiased estimator of the population mean and total, as well as the variance of the mean estimator. We calculated the relative efficiency of the new sampling design to the two-stage cluster sampling with simple random sampling in the

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3

Rodrigues, Josemar. "Asymptotically design-unbiased predictors for two-stage sampling." Statistics & Probability Letters 17, no. 5 (1993): 411–14. http://dx.doi.org/10.1016/0167-7152(93)90263-i.

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4

Vasconcellos, Mauricio Teixeira Leite de, Pedro Luis do Nascimento Silva, and Célia Landmann Szwarcwald. "Sampling design for the World Health Survey in Brazil." Cadernos de Saúde Pública 21, suppl 1 (2005): S89—S99. http://dx.doi.org/10.1590/s0102-311x2005000700010.

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This paper describes the sample design used in the Brazilian application of the World Health Survey. The sample was selected in three stages. First, the census tracts were allocated in six strata defined by their urban/rural situation and population groups of the municipalities (counties). The tracts were selected using probabilities proportional to the respective number of households. In the second stage, households were selected with equiprobability using an inverse sample design to ensure 20 households interviewed per tract. In the last stage, one adult (18 years or older) per household was

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5

Hossaini, Mostafa, and Abdolhamid Rezaei Roknabadi. "Estimation of Subpopulation Parameters in One-stage Cluster Sampling Design." Journal of the Iranian Statistical Society 20, no. 2 (2021): 65–78. http://dx.doi.org/10.52547/jirss.20.2.65.

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Raju, C., and R. Vidya. "DESIGN OF TWO-STAGE CHAIN SAMPLING PLANS WITH KULLBACK-LEIBLER INFORMATION." Advances and Applications in Statistics 73 (January 10, 2022): 47–74. http://dx.doi.org/10.17654/0972361722010.

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7

Fan, Xiang Ning, Hao Zheng, Yu Tao Sun, and Xiang Yan. "Design and Implementation of a 12-Bit 100MS/s ADC." Applied Mechanics and Materials 229-231 (November 2012): 1507–10. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1507.

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In this paper, a 12-bit 100MS/s pipelined ADC is designed. Capacitance flip-around structure is used in sample and hold circuit, and bootstrap structure is adopted in sampling switch which has high linearity. Progressively decreasing technology is used to reduce power consumption and circuit area, where 2.5bit/stage structure is used in the first two stages, 1.5bit/stage structure is used for 3rd to 8th stages, and at the end of the circuit is a 2bit-flash ADC. Digital calibration is designed to eliminate the offset of comparators. Switched-capacitor dynamic comparator structure is used to fur

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8

Valliant, Richard, Jill A. Dever, and Frauke Kreuter. "Effects of Cluster Sizes on Variance Components in Two-Stage Sampling." Journal of Official Statistics 31, no. 4 (2015): 763–82. http://dx.doi.org/10.1515/jos-2015-0044.

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Abstract Determining sample sizes in multistage samples requires variance components for each stage of selection. The relative sizes of the variance components in a cluster sample are dramatically affected by how much the clusters vary in size, by the type of sample design, and by the form of estimator used. Measures of the homogeneity of survey variables within clusters are related to the variance components and affect the numbers of sample units that should be selected at each stage to achieve the desired precision levels. Measures of homogeneity can be estimated using standard software for

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9

Hsu, Lie-Fern, and Jia-Tzer Hsu. "Economic Design of Acceptance Sampling Plans in a Two-Stage Supply Chain." Advances in Decision Sciences 2012 (February 29, 2012): 1–14. http://dx.doi.org/10.1155/2012/359082.

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Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer's and consumer's quality and risk requirements. However, all the available QC tables and computer software determine the sampling plan on a noneconomic basis. In this paper, we design an economic model to determine the opt

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10

Chen, Sixia, David Haziza, and Zeinab Mashreghi. "A Comparison of Existing Bootstrap Algorithms for Multi-Stage Sampling Designs." Stats 5, no. 2 (2022): 521–37. http://dx.doi.org/10.3390/stats5020031.

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Multi-stage sampling designs are often used in household surveys because a sampling frame of elements may not be available or for cost considerations when data collection involves face-to-face interviews. In this context, variance estimation is a complex task as it relies on the availability of second-order inclusion probabilities at each stage. To cope with this issue, several bootstrap algorithms have been proposed in the literature in the context of a two-stage sampling design. In this paper, we describe some of these algorithms and compare them empirically in terms of bias, stability, and

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