LEADER 05496nam 22006974a 450 001 9910143689003321 005 20170815121600.0 010 $a1-280-27623-1 010 $a9786610276233 010 $a0-470-01135-1 010 $a0-470-01134-3 035 $a(CKB)1000000000357448 035 $a(EBL)239034 035 $a(OCoLC)475950123 035 $a(SSID)ssj0000149684 035 $a(PQKBManifestationID)11147462 035 $a(PQKBTitleCode)TC0000149684 035 $a(PQKBWorkID)10239122 035 $a(PQKB)10338256 035 $a(MiAaPQ)EBC239034 035 $a(EXLCZ)991000000000357448 100 $a20050114d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aEstimation in surveys with nonresponse$b[electronic resource] /$fCarl-Erik Sa?rndal, Sixten Lundstro?m 210 $aHoboken, NJ $cWiley$dc2005 215 $a1 online resource (214 p.) 225 1 $aWiley Series in Survey Methodology 300 $aDescription based upon print version of record. 311 $a0-470-01133-5 320 $aIncludes bibliographical references (p. [191]-194) and index. 327 $aEstimation in Surveys with Nonresponse; Contents; Preface; Chapter 1 Introduction; Chapter 2 The Survey and Its Imperfections; 2.1 The survey objective; 2.2 Sources of error in a survey; Chapter 3 General Principles to Assist Estimation; 3.1 Introduction; 3.2 The importance of auxiliary information; 3.3 Desirable features of an auxiliary vector; Chapter 4 The Use of Auxiliary Information under Ideal Conditions; 4.1 Introduction; 4.2 The Horvitz-Thompson estimator; 4.3 The generalized regression estimator; 4.4 Variance and variance estimation 327 $a4.5 Examples of the generalized regression estimatorChapter 5 Introduction to Estimation in the Presence of Nonresponse; 5.1 General background; 5.2 Errors caused by sampling and nonresponse; Appendix: Variance and mean squared error under nonresponse; Chapter 6 Weighting of Data in the Presence of Nonresponse; 6.1 Traditional approaches to weighting; 6.2 Auxiliary vectors and auxiliary information; 6.3 The calibration approach: some terminology; 6.4 Point estimation under the calibration approach; 6.5 Calibration estimators for domains; 6.6 Comments on the calibration approach 327 $a6.7 Alternative sets of calibrated weights6.8 Properties of the calibrated weights; Chapter 7 Examples of Calibration Estimators; 7.1 Examples of familiar estimators for data with nonresponse; 7.2 The simplest auxiliary vector; 7.3 One-way classi.cation; 7.4 A single quantitative auxiliary variable; 7.5 One-way classi.cation combined with a quantitative variable; 7.6 Two-way classi.cation; 7.7 A Monte Carlo simulation study; Chapter 8 The Combined Use of Sample Information and Population Information; 8.1 Options for the combined use of information 327 $a8.2 An example of calibration with information at both levels8.3 A Monte Carlo simulation study of alternative calibration procedures; 8.4 Two-step procedures in practice; Chapter 9 Analysing the Bias due to Nonresponse; 9.1 Simple estimators and their nonresponse bias; 9.2 Finding an ef.cient grouping; 9.3 Further illustrations of the nonresponse; 9.4 A general expression for the bias of the calibration estimator; 9.5 Conditions for near-unbiasedness; 9.6 A review of concepts, terms and ideas; Appendix: Proof of Proposition 9.1; Chapter 10 Selecting the Most Relevant Auxiliary Information 327 $a10.1 Discussion10.2 Guidelines for the construction of an auxiliary vector; 10.3 The prospects for near-zero bias with traditional estimators; 10.4 Further avenues towards a zero bias; 10.5 A further tool for reducing the bias; 10.6 The search for a powerful auxiliary vector; 10.7 Empirical illustrations of the indicators; 10.8 Literature review; Chapter 11 Variance and Variance Estimation; 11.1 Variance estimation for the calibration estimator; 11.2 An estimator for ideal conditions; 11.3 A useful relationship; 11.4 Variance estimation for the two-step A and two-step B procedures 327 $a11.5 A simulation study of the variance estimation technique 330 $aAround the world a multitude of surveys are conducted every day, on a variety of subjects, and consequently surveys have become an accepted part of modern life. However, in recent years survey estimates have been increasingly affected by rising trends in nonresponse, with loss of accuracy as an undesirable result. Whilst it is possible to reduce nonresponse to some degree, it cannot be completely eliminated. Estimation techniques that account systematically for nonresponse and at the same time succeed in delivering acceptable accuracy are much needed. Estimation in Surveys with Nonrespons 410 0$aWiley Series in Survey Methodology 606 $aEstimation theory 606 $aSampling (Statistics) 606 $aNonresponse (Statistics) 608 $aElectronic books. 615 0$aEstimation theory. 615 0$aSampling (Statistics) 615 0$aNonresponse (Statistics) 676 $a001.433 676 $a519.5/44 676 $a519.544 700 $aSa?rndal$b Carl-Erik$f1937-$0102999 701 $aLundstro?m$b Sixten$0614447 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143689003321 996 $aEstimation in surveys with nonresponse$91130860 997 $aUNINA LEADER 04805nam 22007695 450 001 9910299672203321 005 20251116140300.0 010 $a3-319-11023-3 024 7 $a10.1007/978-3-319-11023-3 035 $a(CKB)3710000000311792 035 $a(EBL)1968102 035 $a(SSID)ssj0001408092 035 $a(PQKBManifestationID)11856269 035 $a(PQKBTitleCode)TC0001408092 035 $a(PQKBWorkID)11347745 035 $a(PQKB)10903412 035 $a(DE-He213)978-3-319-11023-3 035 $a(MiAaPQ)EBC1968102 035 $a(PPN)183153863 035 $a(EXLCZ)993710000000311792 100 $a20141205d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Water Resources Engineering /$fedited by Chih Ted Yang, Lawrence K. Wang 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (577 p.) 225 1 $aHandbook of Environmental Engineering,$x2512-1359 ;$v14 300 $aDescription based upon print version of record. 311 08$a3-319-11022-5 320 $aIncludes bibliographical references at the end of each chapters. 327 $a1. Watershed Sediment Dynamics and Modeling: A Watershed Modeling System for the Yellow River -- 2. Integrated Simulation of Interactive Surface Water and Ground Water Systems -- 3. River-Channel Stabilization with Submerged Vanes -- 4. Mathematic Modeling of Non-Equilibrium Sediment Transport, Reservoir Sedimentation, and Fluvial Processes -- 5. Minimum Energy Dissipation Rate Theory and its Applications for Water Resources Engineering -- 6. Hydraulic Modeling Development and Applications in Water Resources -- 7. Geophysical Methods for the Assessment of Earthen Dams -- 8. Soil Erosion on Upland Areas by Rainfall and Overland Flow -- 9. Advances in Geofluvial Modeling: Methodologies and Applications -- 10. Environmental and Water Engineering Glossary. 330 $aThe Handbook of Environmental Engineering is a collection of methodologies that study the effects of pollution and waste in their three basic forms: gas, solid, and liquid. A sister volume to Volume 15: Modern Water Resources Engineering, this volume focuses on the theory and analysis of various water resources systems including watershed sediment dynamics and modeling, integrated simulation of interactive surface water and groundwater systems, river channel stabilization with submerged vanes, non-equilibrium sediment transport, reservoir sedimentation, and fluvial processes, minimum energy dissipation rate theory and applications, hydraulic modeling development and application, geophysical methods for assessment of earthen dams, soil erosion on upland areas by rainfall and overland flow, geofluvial modeling methodologies and applications, and an environmental water engineering glossary. This critical volume will serve as a valuable reference work for advanced undergraduate and graduate students, designers of water resources systems, and scientists and researchers. 410 0$aHandbook of Environmental Engineering,$x2512-1359 ;$v14 606 $aWater$xPollution 606 $aFluid mechanics 606 $aEnvironmental sciences 606 $aEnvironmental engineering 606 $aBiotechnology 606 $aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution$3https://scigraph.springernature.com/ontologies/product-market-codes/U35040 606 $aEngineering Fluid Dynamics$3https://scigraph.springernature.com/ontologies/product-market-codes/T15044 606 $aEnvironmental Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/G37000 606 $aEnvironmental Engineering/Biotechnology$3https://scigraph.springernature.com/ontologies/product-market-codes/U33000 615 0$aWater$xPollution. 615 0$aFluid mechanics. 615 0$aEnvironmental sciences. 615 0$aEnvironmental engineering. 615 0$aBiotechnology. 615 14$aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. 615 24$aEngineering Fluid Dynamics. 615 24$aEnvironmental Science and Engineering. 615 24$aEnvironmental Engineering/Biotechnology. 676 $a333.7 676 $a363.7394 676 $a363.73946 676 $a620.1064 676 $a628 676 $a660.6 702 $aYang$b Chih Ted$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWang$b Lawrence K.$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299672203321 996 $aAdvances in Water Resources Engineering$92507750 997 $aUNINA