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010   $a3-319-50272-7
024 7 $a10.1007/978-3-319-50272-4
035   $a(CKB)3710000001364130
035   $a(DE-He213)978-3-319-50272-4
035   $a(MiAaPQ)EBC4855639
035   $a(PPN)201473984
035   $a(EXLCZ)993710000001364130
100   $a20170505d2017      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aStatistical Disclosure Control for Microdata $eMethods and Applications in R /$fby Matthias Templ
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (XIX, 287 p. 37 illus., 27 illus. in color.)
311 08$a3-319-50270-0 
320   $aIncludes bibliographical references and index.
327   $aPreface -- Software -- Basic Concepts -- Disclosure Risk -- Methods for Data Perturbation -- Data Utility and Information Loss -- Synthetic Data -- Practical Guidelines -- Case Studies -- Solutions -- Index.
330   $aThis book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the dat a before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data. It will also be interesting for researchers working in statistical disclosure control and the health sciences.
606   $aSocial sciences$xStatistical methods
606   $aMathematical statistics$xData processing
606   $aStatistics
606   $aStatistics
606   $aBiometry
606   $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
606   $aStatistics and Computing
606   $aStatistical Theory and Methods
606   $aStatistics in Business, Management, Economics, Finance, Insurance
606   $aBiostatistics
615  0$aSocial sciences$xStatistical methods.
615  0$aMathematical statistics$xData processing.
615  0$aStatistics.
615  0$aStatistics.
615  0$aBiometry.
615 14$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
615 24$aStatistics and Computing.
615 24$aStatistical Theory and Methods.
615 24$aStatistics in Business, Management, Economics, Finance, Insurance.
615 24$aBiostatistics.
676   $a519.5
700   $aTempl$b Matthias$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767411
906   $aBOOK
912   $a9910254282203321
996   $aStatistical Disclosure Control for Microdata$91562330
997   $aUNINA