| 书目名称 | Handling Missing Data in Ranked Set Sampling | | 编辑 | Carlos N. Bouza-Herrera | | 视频video | | | 概述 | Fills the gap in the literature on missing observations for ranked set sampling models.Provides ready-to-use models for dealing with non responses in surveys.Prepares the reader to develop further res | | 丛书名称 | SpringerBriefs in Statistics | | 图书封面 |  | | 描述 | The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of interest. Traditionally, simple random sampling is used to select samples. Most statistical models are supported by the use of samples selected by means of this design. In recent decades, an alternative design has started being used, which, in many cases, shows an improvement in terms of accuracy compared with traditional sampling. It is called Ranked Set Sampling (RSS). A random selection is made with the replacement of samples, which are ordered (ranked). The literature on the subject is increasing due to the potentialities of RSS for deriving more effective alternatives to well-established statistical models. In this work, the use of RSS sub-sampling for obtaining information among the non respondents and different imputation procedures are considered. RSS models are developed as counterparts of well-known simple random sampling (SRS) models. SRS and RSS models for estimating the population using missing data are presented and comp | | 出版日期 | Book 2013 | | 关键词 | 62D05, 62F05, 62F10, 62Pxx, 62F40; estimation of the population mean; imputation of missing observatio | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-39899-5 | | isbn_softcover | 978-3-642-39898-8 | | isbn_ebook | 978-3-642-39899-5Series ISSN 2191-544X Series E-ISSN 2191-5458 | | issn_series | 2191-544X | | copyright | The Author(s) 2013 |
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发表于 2025-3-21 18:59:23
