LEADER 04383nam 22006735 450 001 996418264703316 005 20220623144729.0 010 $a3-030-38164-1 024 7 $a10.1007/978-3-030-38164-6 035 $a(CKB)4100000010480300 035 $a(DE-He213)978-3-030-38164-6 035 $a(MiAaPQ)EBC6126406 035 $a(PPN)242979475 035 $a(EXLCZ)994100000010480300 100 $a20200229d2020 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied multiple imputation$b[electronic resource] $eadvantages, pitfalls, new developments and applications in R /$fby Kristian Kleinke, Jost Reinecke, Daniel Salfrán, Martin Spiess 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XI, 292 p. 20 illus., 3 illus. in color.) 225 1 $aStatistics for Social and Behavioral Sciences,$x2199-7357 311 $a3-030-38163-3 327 $a1 Introduction and Basic Concepts -- 2 Missing Data Mechanism and Ignorability -- 3 Missing Data Methods -- 4 Multiple Imputation: Theory -- 5 Multiple Imputation: Application -- 6 Multiple Imputation: New Developments -- A Appendices -- Index. 330 $aThis book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation. It discusses the pros and cons of various techniques and concepts, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically relevant developments in the field, and demonstrates the use of recent multiple imputation techniques designed for situations where distributional assumptions of the classical multiple imputation solutions are violated. In addition, the book features numerous practical tutorials for widely used R software packages to generate multiple imputations (norm, pan and mice). The provided R code and data sets allow readers to reproduce all the examples and enhance their understanding of the procedures. This book is intended for social and health scientists and other quantitative researchers who analyze incompletely observed data sets, as well as master?s and PhD students with a sound basic knowledge of statistics. . 410 0$aStatistics for Social and Behavioral Sciences,$x2199-7357 606 $aStatistics  606 $aPsychology?Methodology 606 $aPsychological measurement 606 $aR (Computer program language) 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 606 $aPsychological Methods/Evaluation$3https://scigraph.springernature.com/ontologies/product-market-codes/Y20040 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 615 0$aStatistics . 615 0$aPsychology?Methodology. 615 0$aPsychological measurement. 615 0$aR (Computer program language). 615 14$aStatistics for Social Sciences, Humanities, Law. 615 24$aPsychological Methods/Evaluation. 615 24$aStatistics for Life Sciences, Medicine, Health Sciences. 615 24$aStatistical Theory and Methods. 615 24$aStatistics and Computing/Statistics Programs. 676 $a001.422 700 $aKleinke$b Kristian$4aut$4http://id.loc.gov/vocabulary/relators/aut$0971635 702 $aReinecke$b Jost$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSalfrán$b Daniel$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSpiess$b Martin$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418264703316 996 $aApplied Multiple Imputation$92209003 997 $aUNISA LEADER 01609nam 2200445 450 001 9910715295703321 005 20210107091844.0 035 $a(CKB)5470000002509063 035 $a(OCoLC)1229094950 035 $a(EXLCZ)995470000002509063 100 $a20210107d1990 ua 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEvaluation of solidification/stabilization as a best demonstrated available technology for contaminated soils$iProject summary /$fLee Weitzman, Lawrence E. Hamel, and Edwin F. Barth 210 1$aCincinnati, OH :$cUnited States Environmental Protection Agency, Research and Development, Research and Development, Risk Reduction Engineering Laboratory,$d1990. 215 $a1 online resource (5 pages) 300 $a"EPA/600/S2-89/013." 300 $a"Feb. 1990." 517 3 $aProject summary 606 $aSoil pollution 606 $aHazardous wastes$xSolidification 606 $aHazardous wastes$xStabilization 606 $aHazardous waste site remediation 615 0$aSoil pollution. 615 0$aHazardous wastes$xSolidification. 615 0$aHazardous wastes$xStabilization. 615 0$aHazardous waste site remediation. 700 $aWeitzman$b Leo$01421340 702 $aHamel$b Lawrence E. 702 $aBarth$b Edwin F. 712 02$aRisk Reduction Engineering Laboratory (U.S.), 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910715295703321 996 $aEvaluation of solidification$93542307 997 $aUNINA