---

＜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

 類似資料