{"product_id":"statistical-disclosure-control-for-microdata-practical-r","title":"Statistical Disclosure Control for Microdata - Practical R","description":"\u003cp\u003eIn this review of Statistical Disclosure Control for Microdata, the bottom line is clear: researchers and data custodians who need a rigorous, reproducible path to anonymizing microdata will find one comprehensive resource here. The book combines theory, applied methods and R code so readers can move from concepts like disclosure risk to practical implementations with \u003cstrong\u003esdcMicro\u003c\/strong\u003e and \u003cstrong\u003esimPop\u003c\/strong\u003e. It is most valuable to applied statisticians, survey methodologists and privacy practitioners who want worked examples and case studies they can run and adapt.\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eTheory and methods:\u003c\/strong\u003e Presents the foundations of statistical disclosure control so readers understand why particular anonymization methods are used and what trade-offs they imply.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePractical R code:\u003c\/strong\u003e Includes runnable examples and the underlying R code that allow readers to reproduce analyses using \u003cstrong\u003esdcMicro\u003c\/strong\u003e and \u003cstrong\u003esimPop\u003c\/strong\u003e.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDisclosure risk and utility:\u003c\/strong\u003e Explains how to measure disclosure risk alongside information loss, helping users choose methods that balance privacy and data usefulness.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eData perturbation techniques:\u003c\/strong\u003e Covers perturbation and related approaches so practitioners can apply techniques to microdata from surveys or registers.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCase studies with solutions:\u003c\/strong\u003e Provides exercises with solutions and real-world case studies that illustrate end-to-end application of methods.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThis book is ideal for applied statisticians, data managers and academic researchers working with person-level or enterprise microdata who need a thorough, hands-on treatment of anonymization. The presence of R code and case studies makes it suited for users who want to reproduce results or adapt workflows to their datasets.\u003c\/p\u003e\n\u003cp\u003eReaders who seek an introductory primer with minimal mathematics or no programming will find parts of the text dense; likewise, advanced theorists looking for new cutting-edge privacy theorems may prefer more specialized research papers. This book sits squarely between method and practice.\u003c\/p\u003e\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eCombines theoretical background with practical R implementations for direct reproducibility.\u003c\/li\u003e\n\u003cli\u003eIncludes detailed case studies and exercises with solutions to reinforce learning.\u003c\/li\u003e\n\u003cli\u003eExplains both disclosure risk metrics and information loss so users can evaluate trade-offs.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eMaterial assumes familiarity with R, so complete beginners will need prior programming experience.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eStatistical Disclosure Control for Microdata\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthor\u003c\/td\u003e\n\u003ctd\u003eMatthias Templ\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocus\u003c\/td\u003e\n\u003ctd\u003eMethods, applications and software implementation for microdata anonymization\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSoftware covered\u003c\/td\u003e\n\u003ctd\u003esdcMicro and simPop in R\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eIncludes\u003c\/td\u003e\n\u003ctd\u003eExamples, exercises with solutions and case studies with R code\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePrimary topics\u003c\/td\u003e\n\u003ctd\u003eData perturbation, disclosure risk, data utility and synthetic data\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eStatistical Disclosure Control for Microdata is a practical, well-structured resource for professionals who must anonymize microdata and reproduce analyses with R. Its combination of theory, examples and code delivers strong value for applied statisticians and data custodians, though newcomers to R will face a learning curve before leveraging the full benefit.\u003c\/p\u003e\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDoes the book include code I can run?\u003c\/strong\u003e\u003cbr\u003eYes. The text provides the underlying R code and examples using the sdcMicro and simPop packages so readers can reproduce results.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat topics does it cover on privacy?\u003c\/strong\u003e\u003cbr\u003eThe book covers disclosure risk assessment, information loss measures, data perturbation methods and approaches to simulating synthetic data.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWho needs prior knowledge to use this book?\u003c\/strong\u003e\u003cbr\u003eFamiliarity with R and basic statistical concepts is recommended to make full use of the examples and exercises.\u003c\/p\u003e","brand":"Matthias Templ","offers":[{"title":"Default Title","offer_id":48149003862235,"sku":"3319843621","price":64.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/51SHg4Tgn8L._SL1254.jpg?v=1768915760","url":"https:\/\/gearmusthave.com\/products\/statistical-disclosure-control-for-microdata-practical-r","provider":"GearMustHave","version":"1.0","type":"link"}