LEADER 00732nam0-22002771i-450- 001 990003234310403321 010 $a063115003X 035 $a000323431 035 $aFED01000323431 035 $a(Aleph)000323431FED01 035 $a000323431 100 $a20020225d1987----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $a 200 1 $a<>introduction to econometrics$fMichael Pokorny 210 $aOxford$cBSSil Blackwell$d1987 215 $aXI, 436 p.$d23 cm 700 1$aPokorny,$bMichael$0129160 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003234310403321 952 $aB/3.2 POK$b19502$fSES 959 $aSES 996 $aIntroduction to econometrics$943451 997 $aUNINA LEADER 00880nam0-22003011i-450- 001 990005935110403321 005 20090210095107.0 035 $a000593511 035 $aFED01000593511 035 $a(Aleph)000593511FED01 035 $a000593511 100 $a20000112f19301950km-y0itay50------ba 101 0 $afre 102 $aFR 105 $ay---n---001yy 200 1 $a<>Conception spiritualiste et la sociologie criminelle$fC. Picone Chiodo$gtraduit de l'Italien par C. Vesme 210 $aParis$cFicker$d[19..] 215 $a185 p.$d22 cm 676 $a364.2 700 1$aPicone-Chiodo,$bCalogero$0225588 702 1$aVesme,$bC. 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990005935110403321 952 $aMASSARI E 88$b4106$fFGBC 959 $aFGBC 996 $aConception spiritualiste et la sociologie criminelle$9586611 997 $aUNINA LEADER 02453nam 2200541 450 001 9910555108103321 005 20230126221332.0 010 $a1-119-42272-8 010 $a1-119-42273-6 010 $a1-119-42271-X 035 $a(CKB)4100000009184939 035 $a(MiAaPQ)EBC5892451 035 $a(OCoLC-P)1123181408 035 $a(CaSebORM)9781119422709 035 $a(OCoLC)1123181408 035 $a(EXLCZ)994100000009184939 100 $a20191007d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStructural equation modeling $eapplications using Mplus /$fJichuan Wang, Xiaoqian Wang 205 $aSecond edition. 210 1$aHoboken, New Jersey ;$aChichester, West Sussex, England :$cWiley,$d[2020] 210 4$dİ2020 215 $a1 online resource (537 pages) 225 0 $aWiley series in probability and statistics 311 $a1-119-42270-1 320 $aIncludes bibliographical references and index. 327 $aConfirmatory factor analysis -- Structural equation model -- Latent growth models (LGM) for longitudinal data analysis -- Multi-group modeling -- Mixture modeling -- Sample size for structural equation modeling. 330 $aDiscusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this second edition, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book"--$cProvided by publisher 606 $aStructural equation modeling$xData processing 606 $aMultivariate analysis$xData processing 606 $aSocial sciences$xStatistical methods$xData processing 615 0$aStructural equation modeling$xData processing. 615 0$aMultivariate analysis$xData processing. 615 0$aSocial sciences$xStatistical methods$xData processing. 676 $a300.285 700 $aWang$b Jichuan$0960180 702 $aWang$b Xiaoqian 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910555108103321 996 $aStructural equation modeling$92818973 997 $aUNINA