{"product_id":"predicting-recidivism-using-survival-models-rigorous-applied","title":"Predicting Recidivism Using Survival Models - Rigorous Applied","description":"\u003cp\u003eIn this review of Predicting Recidivism Using Survival Models the bottom line is clear: this is a focused, technical monograph for researchers and advanced students interested in applying econometric survival techniques to criminal justice data. The authors describe the origins of their work and why timing and censoring present unique statistical challenges; the book's single biggest reason to buy is its detailed, applied perspective on modeling skewed time-to-event data in recidivism studies. Readers will find a careful methodological narrative rather than a broad textbook introduction.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eApplied survival modeling:\u003c\/strong\u003e The book explains how survival models handle timing and censoring, giving readers concrete context for implementation in recidivism research.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHistorical perspective:\u003c\/strong\u003e Authors recount their development of approaches in the mid 1970s, helping readers appreciate methodological evolution and motivation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEconometric focus:\u003c\/strong\u003e Emphasis on methods from the econometric literature makes the work practical for applied quantitative researchers.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAttention to data issues:\u003c\/strong\u003e The discussion of skewness and censoring provides valuable guidance when confronting real-world criminal justice data.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConcise case orientation:\u003c\/strong\u003e Rather than broad survey material, the book concentrates on a concrete application, which aids reproducibility for similar studies.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eWho It's For\u003c\/h2\u003e\u003cp\u003eThis book is best suited for graduate students, applied statisticians, and criminology researchers who already have a grounding in econometrics or survival analysis and want a focused case study on recidivism timing. It presumes familiarity with quantitative methods and interest in methodological detail rather than introductory explanations.\u003c\/p\u003e\u003cp\u003eThose seeking a beginner-friendly introduction to statistics, a general textbook on criminology, or a collection of policy essays should look elsewhere; this volume is narrow in scope and intended for readers aiming to implement or adapt survival models for event-time data.\u003c\/p\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eProvides a clear applied account of using \u003cstrong\u003esurvival models\u003c\/strong\u003e for recidivism, useful for replication and further study.\u003c\/li\u003e\n\u003cli\u003eExplains data challenges like \u003cstrong\u003ecensoring and skewness\u003c\/strong\u003e, helping readers prepare appropriate analyses.\u003c\/li\u003e\n\u003cli\u003eOffers historical and methodological context that illustrates why specific econometric choices were made.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eThe focused, technical nature means it is not an introductory text and may be dense for newcomers to \u003cstrong\u003eeconometrics\u003c\/strong\u003e.\u003c\/li\u003e\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003ePredicting Recidivism Using Survival Models\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSeries\u003c\/td\u003e\n\u003ctd\u003eResearch in Criminology\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003ePeter Schmidt, Ann D. Witte\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSubject focus\u003c\/td\u003e\n\u003ctd\u003eStatistical modeling of recidivism timing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMethodological emphasis\u003c\/td\u003e\n\u003ctd\u003eSurvival models, econometric methods\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eKey issues discussed\u003c\/td\u003e\n\u003ctd\u003eSkewness and censoring in event-time data\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003ch2\u003eOur Verdict\u003c\/h2\u003e\u003cp\u003ePredicting Recidivism Using Survival Models is a well-focused, methodologically rich volume that pays off for readers seeking a practical application of survival analysis in criminal justice research. It represents good value for graduate researchers and applied statisticians who need a case-oriented treatment of censoring and timing issues rather than a generalist introduction.\u003c\/p\u003e\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDoes this book teach survival model implementation?\u003c\/strong\u003e\u003cbr\u003eThe book emphasizes applied econometric approaches and explains how survival models address timing and censoring, but it assumes prior quantitative background rather than step-by-step software tutorials.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho wrote this volume?\u003c\/strong\u003e\u003cbr\u003eThe work is authored by Peter Schmidt and Ann D. Witte, who describe their development of these methods beginning in the mid 1970s.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eIs this suitable for policy makers?\u003c\/strong\u003e\u003cbr\u003ePolicy makers may find the insights useful, but the book is aimed primarily at researchers and advanced students familiar with econometric concepts.\u003c\/p\u003e","brand":"Peter Schmidt, Ann D. Witte","offers":[{"title":"Default Title","offer_id":48603859714267,"sku":"1461283434","price":87.37,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/51ewUTlyT2L._SL1251.jpg?v=1778351397","url":"https:\/\/gearmusthave.com\/products\/predicting-recidivism-using-survival-models-rigorous-applied","provider":"GearMustHave","version":"1.0","type":"link"}