LEADER 01012nas 2200397 a 450 001 996209660703316 005 20240413021242.0 011 $a1559-0100 035 $a(OCoLC)44539922 035 $a(CKB)954928622307 035 $a(CONSER) 2005215864 035 $a(EXLCZ)99954928622307 100 $a20000706a19949999 sy a 101 0 $aeng 135 $aurcnu---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEndocrine 210 $aTotowa, N.J. $cHumana Press 300 $aRefereed/Peer-reviewed 311 $a1355-008X 606 $aEndocrinology$vPeriodicals 606 $aEndocrine System Diseases 606 $aEndocrine Glands 606 $aHormones 608 $aPeriodical. 615 0$aEndocrinology 615 2$aEndocrine System Diseases. 615 2$aEndocrine Glands. 615 2$aHormones. 676 $a612 906 $aJOURNAL 912 $a996209660703316 996 $aEndocrine$91948232 997 $aUNISA LEADER 01704oas 2200613 a 450 001 9910693459603321 005 20251106213014.0 011 $a2150-1548 035 $a(OCoLC)316796316 035 $a(CONSER) 2009230830 035 $a(CKB)2550000000028242 035 $a(EXLCZ)992550000000028242 100 $a20090323a20099999 ua a 101 0 $afre 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDjibouti perspective de la se?curite? alimentaire 210 $a[Washington, D.C.] $c[FEWS NET] 215 $avolumes $cdigital, PDF file 606 $aFood supply$zDjibouti$vPeriodicals 606 $aFamines$zDjibouti$vPeriodicals 606 $aFamines$2fast$3(OCoLC)fst00920590 606 $aFood supply$2fast$3(OCoLC)fst00931196 607 $aDjibouti$2fast$1https://id.oclc.org/worldcat/entity/E39PBJbWBJw4kXbwcRTpKyCWjC 608 $aPeriodicals.$2fast 608 $aPeriodicals.$2lcgft 615 0$aFood supply 615 0$aFamines 615 7$aFamines. 615 7$aFood supply. 676 $a363 712 02$aFamine Early Warning System Network. 712 02$aUnited States.$bAgency for International Development. 801 0$bGPO 801 1$bGPO 801 2$bGPO 801 2$bDLC 801 2$bOCLCQ 801 2$bOCLCA 801 2$bOCLCF 801 2$bOCLCQ 801 2$bOCLCA 801 2$bGILDS 801 2$bOCLCO 801 2$bOCLCA 801 2$bOCLCQ 801 2$bOCLCL 801 2$bOCLCQ 906 $aJOURNAL 912 $a9910693459603321 996 $aDjibouti perspective de la se?curite? alimentaire$93115960 997 $aUNINA LEADER 05525nam 22007214a 450 001 9911019680603321 005 20251116151750.0 010 $a9786610276233 010 $a9781280276231 010 $a1280276231 010 $a9780470011355 010 $a0470011351 010 $a9780470011348 010 $a0470011343 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(Perlego)2758830 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 /$fCarl-Erik Sarndal, Sixten Lundstrom 210 $aHoboken, NJ $cWiley$dc2005 215 $a1 online resource (214 p.) 225 1 $aWiley Series in Survey Methodology 300 $aDescription based upon print version of record. 311 08$a9780470011331 311 08$a0470011335 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 $aNonresponse (Statistics) 615 0$aEstimation theory. 615 0$aSampling (Statistics) 615 0$aNonresponse (Statistics) 676 $a519.5/44 700 $aSa?rndal$b Carl-Erik$f1937-$0102999 701 $aLundstro?m$b Sixten$0614447 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019680603321 996 $aEstimation in surveys with nonresponse$91130860 997 $aUNINA