6533b831fe1ef96bd1299a51

RESEARCH PRODUCT

Improving the Representativeness of a Simple Random Sample: An Optimization Model and Its Application to the Continuous Sample of Working Lives

Carlos Vidal-meliáMarta Regúlez CastilloJuan Manuel Pérez-salamero GonzálezVicente A. Núñez Antón

subject

General MathematicsPopulation0211 other engineering and technologiessubsamplingSample (statistics)02 engineering and technologyRepresentativeness heuristic:CIENCIAS ECONÓMICAS [UNESCO]Nonlinear programming0502 economics and businessStatisticsComputer Science (miscellaneous)Chi-square testchi-square testp-value050207 economicseducationEngineering (miscellaneous)Mathematicseducation.field_of_study021103 operations researchlcsh:Mathematics05 social sciencesUNESCO::CIENCIAS ECONÓMICASp-valueSimple random samplelcsh:QA1-939Stratified samplingOptimización matemáticacontinuous sample of working livesEconomía públicaoptimization

description

This paper proposes an optimization model for selecting a larger subsample that improves the representativeness of a simple random sample previously obtained from a population larger than the population of interest. The problem formulation involves convex mixed-integer nonlinear programming (convex MINLP) and is, therefore, NP-hard. However, the solution is found by maximizing the size of the subsample taken from a stratified random sample with proportional allocation and restricting it to a p-value large enough to achieve a good fit to the population of interest using Pearson&rsquo

yearjournalcountryeditionlanguage
2020-07-25Mathematics
10.3390/math8081225http://dx.doi.org/10.3390/math8081225