<電子ブック>
Indirect Sampling / by Pierre Lavallée
(Springer Series in Statistics. ISSN:2197568X)
版 | 1st ed. 2007. |
---|---|
出版者 | New York, NY : Springer New York : Imprint: Springer |
出版年 | 2007 |
本文言語 | 英語 |
大きさ | XVI, 256 p : online resource |
著者標目 | *Lavallée, Pierre author SpringerLink (Online service) |
件 名 | LCSH:Social sciences -- Statistical methods
全ての件名で検索
LCSH:Statistics LCSH:Population -- Economic aspects 全ての件名で検索 LCSH:Quality of life LCSH:Demography LCSH:Population LCSH:Sociology -- Methodology 全ての件名で検索 FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy FREE:Statistical Theory and Methods FREE:Population Economics FREE:Quality of Life Research FREE:Population and Demography FREE:Sociological Methods |
一般注記 | Description and Use of the GWSM -- Literature Review -- Properties -- Other Generalisations -- Application in Longitudinal Surveys -- GWSM and Calibration -- Non-response -- GWSM and Record Linkage -- Conclusion Following the classical sampling theory, the survey statistician selects samples of people, businesses or others, in order to obtain the desired information. Drawing the samples is usually done by randomly selecting from a list representing the target population. In practice, this list is often not available. At best, the statistician only has access to a different list, indirectly related to the targeted population. The example of a survey of children where the statistician only has a list of adult persons is a typical case. In this case, the statistician first draws a sample of adults, and for each selected adult, the statistician then identifies his/her children. The survey is done from the latter. This is what is called indirect sampling. When indirect sampling is used jointly with the sampling of clusters of persons (families, for example), many complications arise for the survey statistician. One of the complications relates to the computation of the estimates from the survey. The production of estimates of simple totals or means can then become nightmares for the survey statistician. To solve this problem, the author proposes a simple solution, easy to implement, that is called the generalised weight share method. This book is the reference on indirect sampling and the generalised weight share method. It contains the different developments done by the author on these subjects. The theory surrounding them is presented, but also different possible applications that drive its interest. The reader will find in this book the answer to questions that come, inevitably, when working in a context of indirect sampling. Pierre Lavallée has been a survey statistician at Statistics Canada since 1985. He gas worked in social, business, and agricultural surveys. He has also worked for Eurostat in Luxembourg HTTP:URL=https://doi.org/10.1007/978-0-387-70782-2 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
|
Springer eBooks | 9780387707822 |
|
電子リソース |
|
EB00237586 |
類似資料
この資料の利用統計
このページへのアクセス回数:3回
※2017年9月4日以降