LEADER 03622nam 22006135 450 001 9910255458903321 005 20250505001401.0 010 $a981-10-6557-8 024 7 $a10.1007/978-981-10-6557-6 035 $a(CKB)3790000000544588 035 $a(DE-He213)978-981-10-6557-6 035 $a(MiAaPQ)EBC5214685 035 $z(PPN)258852445 035 $a(PPN)223953903 035 $a(EXLCZ)993790000000544588 100 $a20180102d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Modelling of Survival Data with Random Effects $eH-Likelihood Approach /$fby Il Do Ha, Jong-Hyeon Jeong, Youngjo Lee 205 $a1st ed. 2017. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2017. 215 $a1 online resource (XIV, 283 p. 23 illus.) 225 1 $aStatistics for Biology and Health,$x2197-5671 311 08$a981-10-6555-1 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Classical Survival Analysis -- H-likelihood Approach to Random-E?ects Models -- Simple Frailty Models -- Multi-Component Frailty Models -- Competing Risks Frailty Models -- Variable Selection for Frailty Models -- Mixed-E?ects Survival Models -- Joint Model for Repeated Measures and Survival Data -- Further Topics -- A Formula for ?tting ?xed and random e?ects -- References -- Index. 330 $aThis book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (?frailtyHL?), while the real-world data examples together with an R package, ?frailtyHL? in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to researchers in medical and genetics fields, graduate students, and PhD (bio) statisticians.      . 410 0$aStatistics for Biology and Health,$x2197-5671 606 $aStatistics 606 $aBiometry 606 $aMathematical statistics$xData processing 606 $aStatistical Theory and Methods 606 $aBiostatistics 606 $aStatistics and Computing 615 0$aStatistics. 615 0$aBiometry. 615 0$aMathematical statistics$xData processing. 615 14$aStatistical Theory and Methods. 615 24$aBiostatistics. 615 24$aStatistics and Computing. 676 $a610.72 700 $aHa$b Il Do$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767638 702 $aJeong$b Jong-Hyeon$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLee$b Youngjo$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910255458903321 996 $aStatistical Modelling of Survival Data with Random Effects$91961541 997 $aUNINA