000			03856nam a22005295i 4500
001			978-0-387-70782-2
003			DE-He213
005			20250710084011.0
007			cr nn 008mamaa
008			100301s2007 xxu| s |||| 0|eng d
020			_a9780387707822 _a99780387707822
024	7		_a10.1007/978-0-387-70782-2 _2doi
082	0	4	_a519.5 _223
100	1		_aLavallée, Pierre. _eauthor.
245	1	0	_aIndirect Sampling _h[recurso electrónico] / _cby Pierre Lavallée.
264		1	_aNew York, NY : _bSpringer New York, _c2007.
300			_aXVI, 256 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _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 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.
650		0	_aSTATISTICS.
650		0	_aQUALITY OF LIFE.
650		0	_aMATHEMATICAL STATISTICS.
650		0	_aPOPULATION.
650		0	_aSOCIAL SCIENCES _xMETHODOLOGY.
650		0	_aQUALITY OF LIFE _xRESEARCH.
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 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c58164 _d58164