000 03624nam a22005175i 4500
001 978-981-10-4856-2
003 DE-He213
005 20181204134419.0
007 cr nn 008mamaa
008 170615s2017 si | s |||| 0|eng d
020 _a9789811048562
_9978-981-10-4856-2
024 7 _a10.1007/978-981-10-4856-2
_2doi
040 _aISI Library, Kolkata
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aBUS061000
_2bisacsh
072 7 _aPBT
_2thema
072 7 _aK
_2thema
082 0 4 _a330.015195
_223
100 1 _aQin, Jing.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aBiased Sampling, Over-identified Parameter Problems and Beyond
_h[electronic resource] /
_cby Jing Qin.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2017.
300 _aXVI, 624 p. 5 illus., 1 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aICSA Book Series in Statistics,
_x2199-0980
505 0 _aChapter 1. Some Examples on Biased Sampling Problems -- Chapter 2. Some Results in Parametric Likelihood and Estimating Functions -- Chapter 3. Nonparametric Maximum Likelihood Estimation and Empirical Likelihood Method -- Chapter 4. General Results in Multiple Samples Biased Sampling Problems with Applications in Case and Control and Genetic Epidemiology -- Chapter 5. Outcome Dependent Sampling Problems -- Chapter 6. Missing Data Problem and Causal Inference -- Chapter 7. Applications of Exponential Tilting Models in Finite Mixture Models -- Chapter 8. Applications of Empirical Likelihood Methods in Survey Sampling -- Chapter 9. Some Other Topics.
520 _aThis book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. .
650 0 _aStatistics.
650 0 _aMathematics.
650 0 _aEconomic theory.
650 1 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
_0http://scigraph.springernature.com/things/product-market-codes/S17010
650 2 4 _aApplications of Mathematics.
_0http://scigraph.springernature.com/things/product-market-codes/M13003
650 2 4 _aEconomic Theory/Quantitative Economics/Mathematical Methods.
_0http://scigraph.springernature.com/things/product-market-codes/W29000
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789811048548
776 0 8 _iPrinted edition:
_z9789811048555
830 0 _aICSA Book Series in Statistics,
_x2199-0980
856 4 0 _uhttps://doi.org/10.1007/978-981-10-4856-2
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c427130
_d427130