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001 978-0-387-70782-2
003 DE-He213
005 20160302162634.0
007 cr nn 008mamaa
008 100301s2007 xxu| s |||| 0|eng d
020 _a9780387707822
_9978-0-387-70782-2
024 7 _a10.1007/978-0-387-70782-2
_2doi
050 4 _aQA276-280
072 7 _aJHBC
_2bicssc
072 7 _aSOC027000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aLavall�e, Pierre.
_eauthor.
245 1 0 _aIndirect Sampling
_h[electronic resource] /
_cby Pierre Lavall�e.
264 1 _aNew York, NY :
_bSpringer New York,
_c2007.
300 _aXVI, 256 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Statistics,
_x0172-7397
505 0 _aDescription and Use of the GWSM -- Literature Review -- Properties -- Other Generalisations -- Application in Longitudinal Surveys -- GWSM and Calibration -- Non-response -- GWSM and Record Linkage -- Conclusion.
520 _aFollowing 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 Lavall�e 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.
650 0 _aStatistics.
650 0 _aMedical research.
650 0 _aPopulation.
650 0 _aSocial sciences.
650 0 _aQuality of life.
650 0 _aDemography.
650 1 4 _aStatistics.
650 2 4 _aStatistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aPopulation Economics.
650 2 4 _aQuality of Life Research.
650 2 4 _aDemography.
650 2 4 _aMethodology of the Social Sciences.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387707785
830 0 _aSpringer Series in Statistics,
_x0172-7397
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-70782-2
912 _aZDB-2-SMA
999 _c177893
_d177893