Minimum Variance Stratification

Dalenius, Tore; Hodges, J. L.

doi:10.1080/01621459.1959.10501501

Cited by 275 publications

(162 citation statements)

References 7 publications

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“…Many other authors draw on this assumption, as Dalenius and Hodges [4], Hedlin [6] and Lavallée and Hidiroglou [7], among others.…”

Section: Computational Resultsmentioning

confidence: 99%

“…Node i Node j Arcs (i, j) (3,5), (3,6), (3,7), (4,5), (4,6),(4,7),(5,6),(5,7)} 3 5 9 {(5,9),(6,9),(7,9),(8,9)} Table 2 Arcs associated to the graph of figure 1 If we consider the sequence of arcs (path) defined by {(1, 4), (4, 7)e(7, 9)}, the first strata would be defined by the indexes from 1 to 3, the second would have the indexes from 4 to 6 and the third, the indexes 7 and 8.…”

Section: Stratum Hmentioning

confidence: 99%

“…A well-known method of strata definition was proposed in [4]. This method consists in approximating the distribution of the variable of stratification X in the population using an histogram with various classes, which implies in adopting the hypothesis that the variable of stratification has an uniform distribution [3] in each class.…”

Section: Problem Definitionmentioning

confidence: 99%

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An exact algorithm for the stratification problem with proportional allocation

et al. 2009

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We report a new optimal resolution for the statistical stratification problem under proportional sampling allocation among strata. Consider a finite population of N units, a random sample of n units selected from this population and a number L of strata. Thus, we have to define which units belong to each stratum so as to minimize the variance of a total estimator for one desired variable of interest in each stratum, and consequently reduce the overall variance for such quantity. In order to solve this problem, an exact algorithm based on the concept of minimal path in a graph is proposed and assessed. Computational results using real data from IBGE (Brazilian Central Statistical Office) are provided.

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“…Many other authors draw on this assumption, as Dalenius and Hodges [4], Hedlin [6] and Lavallée and Hidiroglou [7], among others.…”

Section: Computational Resultsmentioning

confidence: 99%

Section: Stratum Hmentioning

confidence: 99%

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An exact algorithm for the stratification problem with proportional allocation

et al. 2009

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“…Una vez jerarquizadas las unidades de estudio se procedió a agruparlas en estratos (muy bajo, bajo, medio, alto y muy alto), que cumplieran con el requisito de ser homogéneos en su interior y heterogéneos entre ellos, lo que implica usar el criterio de mínima varianza, por lo cual en la institución se seleccionó la Técnica de Estratificación Ópti-ma que desarrollaron Dalenius y Hodges (1959). A continuación se presenta la descripción de su proceso para el caso discreto (Cochran, 1980: 171-172).…”

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Revisión de los Índices de marginación elaborados por el Conapo

Coronado¹

2010

EDU

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Palabras clave: índice, marginación, estratificación, mínima varianza, revisión. IntroducciónUna de las principales obligaciones del Consejo Nacional de Población es identificar y determinar las prioridades relacionadas con el volumen, la estructura, la dinámica y la distribución de la población que reside en México. El propósito es lograr que ésta participe justa y equitativamente de los beneficios del desarrollo económico y social (artículo 1 de la ley General de Población, lGP). Para alcanzarlo la institución desarrolla y publica estudios que sirven como apoyo al diseño, la instrumentación y la evaluación de los programas que coadyuvan al mejoramiento de las condiciones económicas, sociales y del medio ambiente. los utilizan constantemente las instituciones de gobierno en sus distintos niveles, en el desarrollo de investigaciones, y además sirven como referencia en múltiples actividades del sector privado.

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“…Neyman (1934) looked into optimum allocation. A method for the iterative improvement of the points of stratification was given and illustrated in Dalenius and Hodges (1959). Bülher and Deutler (1975) presented a method to determine a global optimal solution by linear programming whereas Lavallée and Hidiroglou (1988) tackled the issue of stratification of a highly skewed population.…”

Section: Introductionmentioning

confidence: 99%

Fast balanced sampling for highly stratified population

Hasler

Tillé

2014

Computational Statistics & Data Analysis

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a b s t r a c tBalanced sampling is a very efficient sampling design when the variable of interest is correlated to the auxiliary variables on which the sample is balanced. A procedure to select balanced samples in a stratified population has previously been proposed. Unfortunately, this procedure becomes very slow as the number of strata increases and it even fails to select samples for some large numbers of strata. A new algorithm to select balanced samples in a stratified population is proposed. This new procedure is much faster than the existing one when the number of strata is large. Furthermore, this new procedure makes it possible to select samples for some large numbers of strata, which was impossible with the existing method. Balanced sampling can then be applied on a highly stratified population when only a few units are selected in each stratum. Finally, this algorithm turns out to be valuable for many applications as, for instance, for the handling of nonresponse.

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Minimum Variance Stratification

Cited by 275 publications

References 7 publications

An exact algorithm for the stratification problem with proportional allocation

An exact algorithm for the stratification problem with proportional allocation

Revisión de los Índices de marginación elaborados por el Conapo

Fast balanced sampling for highly stratified population

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