Successive Sampling to Estimate Quantiles with P-Auxiliary Variables

• Published in: Quality & quantity Vol. 42; no. 4; pp. 427 - 443
• Main Authors: Rueda, María Del Mar, Muñoz, Juan Francisco, Arcos, Antonio
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2008; Springer Nature B.V
• Subjects: Bibliographic literature; Distribution; Economics; Longitudinal Studies; Methodology of the Social Sciences; Operations research; Population; Regression analysis; Samples; Sampling; Social Sciences; Statistics; Surveys; Variables; Variance; quantiles; matched and unmatched samples; longitudinal surveys; successive sampling; distribution function
• ISSN: 0033-5177; 1573-7845
• DOI: 10.1007/s11135-006-9052-4

The successive sampling is a known technique that can be used in longitudinal surveys to estimate population parameters and measurements of difference or change of a study variable. The paper discusses the estimation of quantiles for the current occasion based on sampling in two successive occasions and using p -auxiliary variables obtained of the previous occasion. A multivariate ratio estimator from the matched portion is used to provide the optimum estimate of a quantile by weighting the estimates inversely to derived optimum weights. Its properties are studied under large–sample approximation and the expressions of the variances are established. The behavior of these asymptotic variances is analyzed on the basis of data from natural populations. A simulation study is also used to measure the precision of the proposed estimator.