LEADER 03352oam 2200661I 450 001 9910416126603321 005 20180731045331.0 010 $a1-000-21873-2 010 $a0-429-09620-8 010 $a1-4665-0753-5 024 7 $a10.1201/b13902 035 $a(CKB)2670000000333574 035 $a(EBL)1128533 035 $a(OCoLC)829461089 035 $a(SSID)ssj0000832626 035 $a(PQKBManifestationID)11442998 035 $a(PQKBTitleCode)TC0000832626 035 $a(PQKBWorkID)10899299 035 $a(PQKB)10567408 035 $a(MiAaPQ)EBC1128533 035 $a(CaSebORM)9781466507531 035 $a(OCoLC)827944838 035 $a(EXLCZ)992670000000333574 100 $a20180331d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAge-period-cohort analysis $enew models, methods, and empirical applications /$fYang Yang and Kenneth C. Land 205 $a1st edition 210 1$aBoca Raton, Fla. :$cCRC Press,$d2013. 215 $a1 online resource (339 p.) 225 1 $aChapman & Hall/CRC interdisciplinary statistics series 300 $aA Chapman & Hall book. 311 $a1-322-66825-6 311 $a1-4665-0752-7 320 $aIncludes bibliographical references and index. 327 $a1. Introduction -- 2. Why cohort analysis? -- 3. APC analysis of data from three common research designs -- 4. Formalities of the age-period-cohort analysis conundrum and a generalized linear mixed models (GLMM) framework -- 5. APC accounting/multiple classification model, part I : model identification and estimation using the intrinsic estimator -- 6. APC accounting/multiple classification model, part II : empirical applications -- 7. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part I : the basics -- 8. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part II : advanced analyses -- 9. Mixed effects models : hierarchical APC-growth curve analysis of prospective cohort data -- 10. Directions for future research and conclusion. 330 $aAge-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors' collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables d 410 0$aInterdisciplinary statistics. 606 $aCohort analysis 606 $aAge groups$xStatistical methods 608 $aElectronic books. 615 0$aCohort analysis. 615 0$aAge groups$xStatistical methods. 676 $a001.42/2 676 $a001.422 676 $a300.727 700 $aYang$b Yang$f1975,$0891136 701 $aLand$b Kenneth C$034144 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910416126603321 996 $aAge-period-cohort analysis$91990444 997 $aUNINA LEADER 01106nam a22002775i 4500 001 991002176969707536 007 cr nn 008mamaa 008 121227s1973 gw | s |||| 0|eng d 020 $a9783540378068 035 $ab14133234-39ule_inst 040 $aBibl. Dip.le Aggr. Matematica e Fisica - Sez. Matematica$beng 082 04$a511.3$223 245 00$aMetamathematical investigation of intuitionistic arithmetic and analysis$h[e-book] /$cedited by A. S. Troelstra 260 $aBerlin :$bSpringer,$c1973 300 $a1 online resource (xx, 488 p.) 440 0$aLecture Notes in Mathematics,$x0075-8434 ;$v344 650 0$aMathematics 650 0$aLogic, Symbolic and mathematical 700 1 $aTroelstra, A. S. 773 0 $aSpringer eBooks 856 40$uhttp://dx.doi.org/10.1007/BFb0066739$zAn electronic book accessible through the World Wide Web 907 $a.b14133234$b03-03-22$c05-09-13 912 $a991002176969707536 996 $aMetamathematical investigation of intuitionistic arithmetic and analysis$981460 997 $aUNISALENTO 998 $ale013$b05-09-13$cm$d@ $e-$feng$ggw $h0$i0