Luận án Phân tích các nhân tố tác động tới giá bất động sản trong việc thực hiện chính sách tài chính - Nghiên cứu trên địa bàn thành phố Hà Nội

8,2 12,4 5,8 11,8 6,0 7,8 10,6 8,3% 5 Tính bền vững của BĐS Khả năng đầu tư và thương mại 2 2 2 3 1 2 3 4 2 1 3 2 27 32,5 Mức độ rủi ro về pháp lý 2 1 1 2 2 3 1 1 3 2 2 1 21 25,3 Mức độ rủi ro về môi trường 2 4 1 1 2 3 5 2 1 0 2 2 25 30,1 Thương hiệu và uy tín người khai thác 0 0 0 0 2 1 3 1 0 1 1 1 10 12,1 Tần số 6 7 4 6 7 9 12 8 6 4 8 6 83 100 Tần suất (%) 11,1 13,5 9,8 11,6 12,7 18,3 18,5 15,4 11,8 8,0 15,6 12,8 13,3% 6 Các nhân tố gắn với quá trình đánh giá giá trị BĐS Tình hình thị trường 2 3 1 2 3 1 2 1 0 2 3 2 22 24,2 Mức giá thị trường 1 1 0 1 2 0 0 2 1 0 2 1 11 12,0 Thông tin về thị trường 1 2 1 2 4 3 4 2 1 3 4 2 29 31,9 5 Stt Chủ đề NTL 1 NTL 2 NTL 3 NTL 4 NTL 5 NTL 6 NTL 7 NTL 8 NTL 9 NTL 10 NTL 11 NTL 12 Tần số Tần suất (%) Năng lực người định giá 1 2 1 3 2 2 2 1 1 1 2 1 19 20,9 Phương pháp 1 1 0 1 1 0 1 1 1 1 1 1 10 11,0 Tần số 6 9 3 9 12 6 9 7 4 7 12 7 91 100 Tần suất (%) 11,1 17,3 7,3 17,3 21,8 12,2 13,8 13,5 7,8 14,0 23,5 14,9 14,6% Tổng số lần nhắc 54 52 41 52 55 49 65 52 51 50 51 47 625 100% 6 Phụ lục số 04: Phiếu khảo sát PHIẾU KHẢO SÁT DOANH NGHIỆP/ TỔ CHỨC THAM GIA THỊ TRƯỜNG BẤT ĐỘNG SẢN TRÊN ĐỊA BÀN HÀ NỘI THÔNG TIN CHỈ ĐƯỢC DÙNG VÀO MỤC ĐÍCH NGHIÊN CỨU VÀ ĐƯỢC GIỮ KÍN Đính danh thiếp của người được phỏng vấn lên đầu trang bên phải của bảng hỏi. I. THÔNG TIN 1. Mã số: __________ 2. Ngày ghi phiếu: _________________________________ 3. Họ tên người trả lời phiếu: _________________________________ Chức vụ: _______________________________________________ Điện thoại di động: ___________ Điện thoại văn phòng: _____________ Email: _________________ II. THÔNG TIN CHUNG VỀ DOANH NGHIỆP Một số thông tin có thể điền trước khi phỏng vấn hoặc sau khi phỏng vấn nếu có danh thiếp đính kèm. 1. Tên công ty: ________________________________ 2. Lĩnh vực sản xuất kinh doanh của công ty 1. Bất động sản 2. Sản xuất 3. Thương mại – Dịch vụ 4. Xây dựng 5. Khác (ghi cụ thể_________________________ 7 3. Địa chỉ công ty: 4. Điện thoại:_________ Fax: __________ E-mail: _____________ 5. Năm bắt đầu sản xuất kinh doanh: ____________ 6. Loại hình doanh nghiệp 1. Nhà nước 2. TNHH Một thành viên 3. Cổ phần 4. Liên doanh 5. Nước ngoài 6. Tư nhân 7. Khác (nêu cụ thể)__ 6. Qui mô vốn sở hữu 1. Dưới 100 tỷ đồng 2. Từ 100 đến 200 tỷ đồng 3. Trên 200 tỷ đồng 7. Phạm vi hoạt động 1. Hà Nội 2. Miền Bắc 3. Toàn quốc III. NỘI DUNG CÂU HỎI Xin anh/chị vui lòng trả lời các câu hỏi dưới đây bằng cách khoanh tròn vào các mức điểm tương ứng với mức độ đồng ý của anh/chị (1- Hoàn toàn không đồng ý; 2- Không đồng ý; 3- Bình thường (trung lập); 4- Đồng ý; 5- Hoàn toàn đồng ý ) về các nội dung sau: M ã câu hỏi Nội dung câu hỏi Mức độ đồng ý I. Biến số gắn liền với đặc điểm của BĐS VL1 Khi tìm kiếm BĐS cho doanh nghiệp, Anh/ Chị quan tâm đến diện tích mảnh đất? 1 2 3 4 5 VL2 Anh/ Chị rất quan tâm đối với sự thuận lợi cho đầu tư, xây dựng của mảnh đất? 1 2 3 4 5 VL3 Giá trị công trình trên đất thường được Anh/ Chị tính đến khi kinh doanh BĐS? 1 2 3 4 5 8 M ã câu hỏi Nội dung câu hỏi Mức độ đồng ý VL4 Cơ sở hạ tầng (giao thông, viễn thông, điện) có vai trò rất quan trọng khi tìm mua hay thuê BĐS cho công ty? 1 2 3 4 5 II. Các biến số gắn liền với vị trí của BĐS VT1 Anh/ Chị cho rằng khoảng cách đến trung tâm - hồ Hoàn Kiếm quyết định giá trị BĐS? 1 2 3 4 5 VT2 Giá trị BĐS phụ thuộc vào mức độ thuận lợi cho kinh doanh, sinh hoạt? 1 2 3 4 5 VT3 Mật độ giao thông có ảnh hưởng đến giá trị BĐS? 1 2 3 4 5 VT4 Ví trí BĐS nằm trên trục giao thông chính của khu vực có ảnh hưởng đáng kể đến giá trị của BĐS đó? 1 2 3 4 5 III. Các biến số môi trường xung quanh BĐS MT1 Khi mua hay thuê BĐS cho đơn vị, Anh/ Chị rất quan tâm đến dân trí của khu vực xung quanh? 1 2 3 4 5 MT2 Giá trị BĐS phụ thuộc vào an ninh của khu vực xung quanh? 1 2 3 4 5 MT3 Theo Anh/ Chị, môi trường sinh thái, không gian của khu vực xung quanh có ảnh hưởng đáng kể đến giá trị BĐS dự định mua hay thuê? 1 2 3 4 5 MT4 Khi mua hay thuê BĐS cho đơn vị, Anh/ Chị thường quan tâm đến các dịch vụ giáo dục, y tế? 1 2 3 4 5 MT5 Anh/ Chị có cho rằng giá trị BĐS thay đổi theo các dịch vụ thương mại, mua sắm ở xung quanh? 1 2 3 4 5 MT6 Anh/ Chị ít quan tâm đến các dịch vụ thể thao, giải trí khi mua hay thuê BĐS cho đơn vị? 1 2 3 4 5 IV Các biến số hình ảnh HA1 Anh / Chị có đồng ý là giá trị BĐS phụ thuộc vào thương hiệu và uy tín của người chủ/ người bán BĐS? 1 2 3 4 5 HA2 Theo Anh/ Chị, bản chất và đặc điểm của người chủ/ người bán BĐS có ảnh hưởng quyết định đến giá trị BĐS? 1 2 3 4 5 HA3 Giá trị BĐS thay đổi theo mục đích của người mua? 1 2 3 4 5 9 M ã câu hỏi Nội dung câu hỏi Mức độ đồng ý HA4 Kinh nghiệm và năng lực của người mua BĐS là nhân tó có tác động mạnh đến giá trị của BĐS? 1 2 3 4 5 V Tính bền vững BV1 Giá trị của BĐS thay đổi tùy thuộc vào khả năng đầu tư và khai thác BĐS đó trong tương lai? 1 2 3 4 5 BV2 Theo Anh/ Chị, rủi ro về pháp lý của BĐS trong tương lai sẽ làm giảm giá trị của nó? 1 2 3 4 5 BV3 Mức độ rủi ro về môi trường trong tương lai có ảnh hưởng đến giá trị của BĐS? 1 2 3 4 5 BV4 Thương hiệu và uy tín của người mua BĐS có ảnh hưởng đến giá trị BĐS? 1 2 3 4 5 VI Phương pháp và năng lực định giá BĐS PP Phương pháp định giá BĐS có tác động đáng kể đến giá trị BĐS? 1 2 3 4 5 NL Năng lực đội ngũ định giá có ảnh hưởng to lớn đến giá trị BĐS? 1 2 3 4 5 TT Hệ thống thông tin thị trường BĐS có tác động đáng kể đến mức độ chính xác của giá trị BĐS? 1 2 3 4 5 VII Giá trị BĐS GT1 Giá trị BĐS có ảnh hưởng mạnh mẽ đế giá cả BĐS (hay giá trị ước tính BĐS) và do đó, đến nguồn thu ngân sách từ BĐS? 1 2 3 4 5 GT2 Giá cả BĐS (hay giá trị ước tính BĐS) có ảnh hưởng quyết định đến nguồn thu liên quan đến BĐS? 1 2 3 4 5 10 Phụ lục số 05: Các công văn của cơ quan quản lý nhà nước 11 12 13 14 Phụ lục số 06: Phân tích nhân tố khẳng định CFA - AMOS Number of variables in your model: 52 Number of observed variables: 23 Number of unobserved variables: 29 Number of exogenous variables: 29 Number of endogenous variables: 23 Weights Covariances Variances Means Intercepts Total Fixed 29 0 0 0 0 29 Labeled 0 0 0 0 0 0 Unlabeled 17 17 29 0 0 63 Total 46 17 29 0 0 92 Number of distinct sample moments: 276 Number of distinct parameters to be estimated: 63 Degrees of freedom (276 - 63): 213 Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates Regression Weights: (Group number 1 - Default model) Estimate S.E. C.R. P Label VL1 <--- VL_MT 1.000 VL2 <--- VL_MT 1.011 .050 20.406 *** VL4 <--- VL_MT 1.150 .064 17.987 *** VT1 <--- VT 1.000 VT2 <--- VT 1.249 .061 20.408 *** VT4 <--- VT .975 .049 19.930 *** HA1 <--- HA 1.000 HA2 <--- HA 1.379 .078 17.744 *** HA3 <--- HA 1.405 .105 13.379 *** HA4 <--- HA 1.401 .106 13.260 *** BV1 <--- BV 1.000 BV2 <--- BV 1.212 .073 16.629 *** BV3 <--- BV 1.123 .067 16.642 *** BV4 <--- BV 1.047 .068 15.341 *** PP <--- PP_NL 1.000 NL <--- PP_NL 1.279 .072 17.832 *** TT <--- PP_NL 1.074 .062 17.319 *** GT1 <--- Gg 1.000 GT2 <--- Gg .846 .047 17.848 *** 15 Estimate S.E. C.R. P Label MT1 <--- VL_MT 1.098 .065 16.817 *** MT2 <--- VL_MT .985 .061 16.190 *** MT3 <--- VL_MT .972 .061 16.011 *** MT5 <--- VL_MT .806 .055 14.595 *** Standardized Regression Weights: (Group number 1 - Default model) Estimate VL1 <--- VL_MT .636 VL2 <--- VL_MT .697 VL4 <--- VL_MT .774 VT1 <--- VT .684 VT2 <--- VT .925 VT4 <--- VT .759 HA1 <--- HA .541 HA2 <--- HA .700 HA3 <--- HA .730 HA4 <--- HA .712 BV1 <--- BV .648 BV2 <--- BV .713 BV3 <--- BV .714 BV4 <--- BV .640 PP <--- PP_NL .669 NL <--- PP_NL .757 TT <--- PP_NL .725 GT1 <--- Gg .852 GT2 <--- Gg .716 MT1 <--- VL_MT .704 MT2 <--- VL_MT .669 MT3 <--- VL_MT .660 MT5 <--- VL_MT .587 Covariances: (Group number 1 - Default model) Estimate S.E. C.R. P Label PP_NL Gg .293 .025 11.806 *** VL_MT Gg .167 .021 7.785 *** BV Gg .205 .021 9.857 *** HA BV .135 .017 8.045 *** BV PP_NL .207 .020 10.502 *** VT HA .049 .016 3.120 .002 HA Gg .184 .022 8.528 *** HA PP_NL .226 .023 9.976 *** VL_MT HA .032 .015 2.231 .026 VL_MT BV .215 .020 10.494 *** VT BV .039 .016 2.529 .011 16 Estimate S.E. C.R. P Label VT PP_NL .068 .018 3.891 *** VL_MT VT .086 .018 4.777 *** VT Gg .214 .024 9.007 *** VL_MT PP_NL .121 .018 6.832 *** e1 e2 .158 .021 7.420 *** e12 e13 .281 .030 9.229 *** Correlations: (Group number 1 - Default model) Estimate PP_NL Gg .667 VL_MT Gg .360 BV Gg .512 HA BV .460 BV PP_NL .636 VT HA .133 HA Gg .465 HA PP_NL .702 VL_MT HA .096 VL_MT BV .628 VT BV .105 VT PP_NL .166 VL_MT VT .197 VT Gg .423 VL_MT PP_NL .323 e1 e2 .317 e12 e13 .445 Variances: (Group number 1 - Default model) Estimate S.E. C.R. P Label VL_MT .396 .041 9.734 *** VT .476 .044 10.701 *** HA .289 .039 7.508 *** BV .296 .030 9.768 *** PP_NL .358 .035 10.158 *** Gg .540 .042 12.823 *** e1 .583 .032 18.333 *** e2 .428 .024 17.507 *** e3 .350 .022 15.812 *** e9 .542 .031 17.668 *** e10 .125 .025 5.041 *** e11 .332 .022 15.179 *** e12 .699 .039 18.129 *** e13 .571 .037 15.371 *** e14 .499 .035 14.422 *** 17 Estimate S.E. C.R. P Label e15 .552 .037 15.073 *** e16 .409 .023 17.531 *** e17 .420 .026 16.092 *** e18 .359 .022 16.071 *** e19 .469 .027 17.678 *** e20 .442 .026 17.133 *** e22 .435 .030 14.580 *** e23 .373 .024 15.725 *** e24 .204 .026 7.806 *** e25 .367 .025 14.821 *** e4 .487 .028 17.543 *** e5 .473 .026 18.113 *** e6 .485 .027 18.251 *** e8 .488 .026 19.062 *** Squared Multiple Correlations: (Group number 1 - Default model) Estimate MT5 .345 MT3 .435 MT2 .448 MT1 .495 GT2 .513 GT1 .725 TT .525 NL .574 PP .447 BV4 .409 BV3 .510 BV2 .509 BV1 .420 HA4 .507 HA3 .533 HA2 .490 HA1 .293 VT4 .577 VT2 .856 VT1 .468 VL4 .600 VL2 .486 VL1 .405 M.I. Par Change e6 PP_NL 21.959 .059 e6 e8 19.419 .080 18 M.I. Par Change e5 HA 49.571 .088 e19 HA 24.027 .062 e16 e18 17.121 -.063 e15 e5 26.119 .106 e13 Gg 15.545 .063 e3 e23 19.937 .068 e2 e3 21.997 .068 M.I. Par Change M.I. Par Change MT3 <--- Gg 19.491 .166 MT3 <--- PP_NL 37.280 .281 MT3 <--- HA 21.223 .240 MT3 <--- GT2 24.306 .142 MT3 <--- TT 16.751 .116 MT3 <--- NL 39.315 .155 MT3 <--- PP 27.038 .146 MT3 <--- HA2 17.778 .100 MT2 <--- HA 24.594 .256 MT2 <--- HA4 40.258 .149 MT2 <--- HA2 17.978 .099 MT2 <--- HA1 24.191 .123 MT1 <--- PP_NL 15.323 -.183 MT1 <--- TT 16.732 -.118 MT1 <--- BV1 15.761 -.120 TT <--- VL4 23.563 .120 NL <--- VL_MT 17.926 -.185 NL <--- MT5 26.912 -.154 NL <--- MT2 14.486 -.105 NL <--- VL1 14.505 -.099 BV4 <--- HA 22.376 .245 BV4 <--- HA4 26.018 .120 BV4 <--- HA2 23.674 .114 BV4 <--- HA1 15.491 .098 BV2 <--- HA 16.630 -.207 BV2 <--- HA4 18.721 -.100 HA4 <--- MT2 18.747 .133 HA3 <--- VL1 17.146 -.115 HA2 <--- VL4 16.667 -.107 HA1 <--- BV 23.588 .251 HA1 <--- VL_MT 29.859 .239 HA1 <--- MT3 15.630 .109 HA1 <--- MT2 27.059 .144 19 M.I. Par Change HA1 <--- MT1 22.296 .123 HA1 <--- BV2 18.508 .119 HA1 <--- VL4 23.007 .131 VT4 <--- MT2 16.948 .094 VL4 <--- VL2 15.919 .098 VL2 <--- HA1 15.459 -.087 VL1 <--- HA 17.766 -.221 VL1 <--- HA3 23.726 -.118 Iteratio n Negative eigenvalu es Conditio n # Smallest eigenvalu e Diamete r F NTrie s Ratio 0 e 17 -.903 9999.000 8631.59 5 0 9999.00 0 1 e * 15 -.166 2.302 5486.173 20 .420 2 e * 0 6311.383 2.026 2500.88 6 4 .700 3 e 0 427.510 1.270 2295.245 5 .000 4 e 0 789.952 1.279 1663.114 2 .000 5 e 0 530.594 .976 1000.997 1 1.081 6 e 0 547.099 .335 849.086 1 1.152 7 e 0 550.890 .212 833.678 1 1.101 8 e 0 512.527 .049 833.045 1 1.045 9 e 0 503.966 .005 833.041 1 1.006 10 e 0 505.668 .000 833.041 1 1.000 Model NPAR CMIN DF P CMIN/DF Default model 63 833.041 213 .000 3.911 Saturated model 276 .000 0 Independence model 23 8384.878 253 .000 33.142 Model RMR GFI AGFI PGFI Default model .049 .922 .899 .711 Saturated model .000 1.000 Independence model .237 .363 .305 .332 Model NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI Default model .901 .882 .924 .909 .924 Saturated model 1.000 1.000 1.000 Independence model .000 .000 .000 .000 .000 20 Model PRATIO PNFI PCFI Default model .842 .758 .778 Saturated model .000 .000 .000 Independence model 1.000 .000 .000 Model NCP LO 90 HI 90 Default model 620.041 535.112 712.528 Saturated model .000 .000 .000 Independence model 8131.878 7836.104 8433.994 Model FMIN F0 LO 90 HI 90 Default model .963 .717 .619 .824 Saturated model .000 .000 .000 .000 Independence model 9.694 9.401 9.059 9.750 Model RMSEA LO 90 HI 90 PCLOSE Default model .058 .054 .062 .001 Independence model .193 .189 .196 .000 Model AIC BCC BIC CAIC Default model 959.041 962.637 1259.166 1322.166 Saturated model 552.000 567.753 1866.832 2142.832 Independence model 8430.878 8432.190 8540.447 8563.447 Model ECVI LO 90 HI 90 MECVI Default model 1.109 1.011 1.216 1.113 Saturated model .638 .638 .638 .656 Independence model 9.747 9.405 10.096 9.748 Model HOELTER .05 HOELTER .01 Default model 258 275 Independence model 31 32 Minimization: .054 Miscellaneous: 3.351 Bootstrap: .000 Total: 3.405 21 Phụ lục số 07: Phân tích SEM _ AMOS Number of variables in your model: 53 Number of observed variables: 23 Number of unobserved variables: 30 Number of exogenous variables: 29 Number of endogenous variables: 24 Weights Covariances Variances Means Intercepts Total Fixed 30 0 0 0 0 30 Labeled 0 0 0 0 0 0 Unlabeled 22 12 29 0 0 63 Total 52 12 29 0 0 93 Number of distinct sample moments: 276 Number of distinct parameters to be estimated: 63 Degrees of freedom (276 - 63): 213 Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates Regression Weights: (Group number 1 - Default model) Estimate S.E. C.R. P Label GT. <--- VL_MT .116 .058 2.012 .044 GT. <--- VT .334 .038 8.847 *** GT. <--- HA .208 .054 3.833 *** GT. <--- BV .157 .074 2.109 .035 GT. <--- PP_NL .492 .046 10.675 *** VL1 <--- VL_MT 1.000 VL2 <--- VL_MT .968 .050 19.388 *** VL4 <--- VL_MT 1.123 .063 17.767 *** VT1 <--- VT 1.000 VT2 <--- VT 1.239 .061 20.440 *** VT4 <--- VT .976 .049 19.992 *** HA1 <--- HA 1.000 HA2 <--- HA 1.332 .074 17.946 *** HA3 <--- HA .973 .102 9.576 *** HA4 <--- HA .991 .104 9.557 *** 22 Estimate S.E. C.R. P Label BV1 <--- BV 1.000 BV2 <--- BV 1.140 .070 16.316 *** BV3 <--- BV 1.115 .069 16.223 *** BV4 <--- BV .970 .065 15.016 *** PP <--- PP_NL 1.000 NL <--- PP_NL 1.254 .077 16.247 *** TT <--- PP_NL .979 .062 15.791 *** GT1 <--- GT. 1.000 GT2 <--- GT. .855 .057 14.972 *** MT1 <--- VL_MT 1.103 .065 16.983 *** MT2 <--- VL_MT .991 .061 16.385 *** MT3 <--- VL_MT .942 .060 15.657 *** MT5 <--- VL_MT .775 .055 14.107 *** Standardized Regression Weights: (Group number 1 - Default model) Estimate GT. <--- VL_MT .110 GT. <--- VT .345 GT. <--- HA .200 GT. <--- BV .135 GT. <--- PP_NL .456 VL1 <--- VL_MT .642 VL2 <--- VL_MT .676 VL4 <--- VL_MT .763 VT1 <--- VT .686 VT2 <--- VT .921 VT4 <--- VT .762 HA1 <--- HA .645 HA2 <--- HA .807 HA3 <--- HA .603 HA4 <--- HA .600 BV1 <--- BV .687 BV2 <--- BV .711 BV3 <--- BV .751 BV4 <--- BV .628 PP <--- PP_NL .695 NL <--- PP_NL .772 TT <--- PP_NL .686 GT1 <--- GT. .825 GT2 <--- GT. .689 23 Estimate MT1 <--- VL_MT .713 MT2 <--- VL_MT .680 MT3 <--- VL_MT .645 MT5 <--- VL_MT .570 Covariances: (Group number 1 - Default model) Estimate S.E. C.R. P Label VT HA .050 .019 2.628 .009 VL_MT HA .045 .018 2.522 .012 VL_MT VT .088 .018 4.810 *** VL_MT BV .223 .021 10.566 *** VT BV .042 .016 2.626 .009 HA BV .173 .020 8.467 *** e1 e2 .157 .021 7.498 *** e14 e15 .207 .041 5.064 *** e12 e13 .132 .049 2.672 .008 e2 e3 .072 .017 4.198 *** e6 e8 .083 .020 4.150 *** e16 e18 -.085 .018 -4.757 *** Correlations: (Group number 1 - Default model) Estimate VT HA .112 VL_MT HA .110 VL_MT VT .200 VL_MT BV .610 VT BV .106 HA BV .467 e1 e2 .309 e14 e15 .296 e12 e13 .278 e2 e3 .178 e6 e8 .165 e16 e18 -.245 Variances: (Group number 1 - Default model) Estimate S.E. C.R. P Label VL_MT .403 .041 9.809 *** VT .479 .045 10.737 *** HA .411 .057 7.235 *** 24 Estimate S.E. C.R. P Label BV .333 .033 9.932 *** PP_NL .386 .038 10.072 *** e27 .231 .028 8.218 *** e1 .575 .032 18.131 *** e2 .449 .026 17.115 *** e3 .365 .024 15.442 *** e9 .539 .031 17.595 *** e10 .132 .025 5.324 *** e11 .329 .022 15.020 *** e12 .577 .050 11.501 *** e13 .392 .064 6.156 *** e14 .681 .048 14.308 *** e15 .716 .050 14.394 *** e16 .373 .025 15.042 *** e17 .423 .026 16.225 *** e18 .319 .024 13.275 *** e19 .481 .027 18.051 *** e20 .413 .028 14.759 *** e22 .412 .036 11.434 *** e23 .415 .028 15.075 *** e24 .210 .027 7.639 *** e25 .363 .026 14.195 *** e4 .473 .028 16.968 *** e5 .461 .026 17.632 *** e6 .502 .028 18.029 *** e8 .504 .027 18.856 *** Squared Multiple Correlations: (Group number 1 - Default model) Estimate GT. .486 MT5 .325 MT3 .416 MT2 .463 MT1 .509 GT2 .475 GT1 .681 TT .471 NL .596 PP .483 BV4 .394 25 Estimate BV3 .565 BV2 .505 BV1 .472 HA4 .360 HA3 .364 HA2 .651 HA1 .416 VT4 .581 VT2 .848 VT1 .471 VL4 .582 VL2 .457 VL1 .412 Matrices (Group number 1 - Default model) Factor Score Weights (Group number 1 - Default model) MT5 MT3 MT2 MT1 GT2 GT1 TT NL PP BV4 BV3 BV2 BV1 HA4 HA3 HA2 HA1 VT4 VT2 VT1 VL4 VL2 VL1 PP_NL -.001 -.001 -.002 -.002 .037 .075 .201 .259 .206 -.002 -.006 -.003 -.005 -.003 -.003 -.007 -.002 -.006 -.018 -.004 -.003 -.001 -.001 BV .012 .016 .020 .022 .010 .020 -.003 -.004 -.003 .105 .233 .140 .193 .011 .011 .031 .011 -.003 -.008 -.002 .027 .011 .013 HA -.005 -.007 -.009 -.009 .019 .037 -.006 -.007 -.006 .021 .046 .028 .038 .102 .106 .293 .099 .001 .004 .001 -.011 -.005 -.006 VT .002 .002 .003 .003 .015 .031 -.005 -.006 -.005 -.002 -.004 -.002 -.003 .000 .000 .001 .000 .157 .498 .098 .004 .002 .002 VL_MT .075 .099 .128 .138 .007 .014 -.002 -.003 -.002 .019 .042 .025 .035 -.004 -.004 -.012 -.004 .004 .013 .003 .169 .072 .084 GT. .004 .005 .006 .007 .224 .452 .037 .048 .038 .008 .018 .011 .015 .008 .009 .024 .008 .020 .062 .012 .008 .004 .004 Total Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .492 .157 .208 .334 .116 .000 MT5 .000 .000 .000 .000 .775 .000 MT3 .000 .000 .000 .000 .942 .000 MT2 .000 .000 .000 .000 .991 .000 MT1 .000 .000 .000 .000 1.103 .000 GT2 .421 .134 .178 .285 .099 .855 GT1 .492 .157 .208 .334 .116 1.000 TT .979 .000 .000 .000 .000 .000 NL 1.254 .000 .000 .000 .000 .000 PP 1.000 .000 .000 .000 .000 .000 BV4 .000 .970 .000 .000 .000 .000 BV3 .000 1.115 .000 .000 .000 .000 BV2 .000 1.140 .000 .000 .000 .000 BV1 .000 1.000 .000 .000 .000 .000 HA4 .000 .000 .991 .000 .000 .000 HA3 .000 .000 .973 .000 .000 .000 26 PP_NL BV HA VT VL_MT GT. HA2 .000 .000 1.332 .000 .000 .000 HA1 .000 .000 1.000 .000 .000 .000 VT4 .000 .000 .000 .976 .000 .000 VT2 .000 .000 .000 1.239 .000 .000 VT1 .000 .000 .000 1.000 .000 .000 VL4 .000 .000 .000 .000 1.123 .000 VL2 .000 .000 .000 .000 .968 .000 VL1 .000 .000 .000 .000 1.000 .000 Standardized Total Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .456 .135 .200 .345 .110 .000 MT5 .000 .000 .000 .000 .570 .000 MT3 .000 .000 .000 .000 .645 .000 MT2 .000 .000 .000 .000 .680 .000 MT1 .000 .000 .000 .000 .713 .000 GT2 .314 .093 .138 .238 .076 .689 GT1 .377 .112 .165 .285 .091 .825 TT .686 .000 .000 .000 .000 .000 NL .772 .000 .000 .000 .000 .000 PP .695 .000 .000 .000 .000 .000 BV4 .000 .628 .000 .000 .000 .000 BV3 .000 .751 .000 .000 .000 .000 BV2 .000 .711 .000 .000 .000 .000 BV1 .000 .687 .000 .000 .000 .000 HA4 .000 .000 .600 .000 .000 .000 HA3 .000 .000 .603 .000 .000 .000 HA2 .000 .000 .807 .000 .000 .000 HA1 .000 .000 .645 .000 .000 .000 VT4 .000 .000 .000 .762 .000 .000 VT2 .000 .000 .000 .921 .000 .000 VT1 .000 .000 .000 .686 .000 .000 VL4 .000 .000 .000 .000 .763 .000 VL2 .000 .000 .000 .000 .676 .000 VL1 .000 .000 .000 .000 .642 .000 Direct Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .492 .157 .208 .334 .116 .000 MT5 .000 .000 .000 .000 .775 .000 27 PP_NL BV HA VT VL_MT GT. MT3 .000 .000 .000 .000 .942 .000 MT2 .000 .000 .000 .000 .991 .000 MT1 .000 .000 .000 .000 1.103 .000 GT2 .000 .000 .000 .000 .000 .855 GT1 .000 .000 .000 .000 .000 1.000 TT .979 .000 .000 .000 .000 .000 NL 1.254 .000 .000 .000 .000 .000 PP 1.000 .000 .000 .000 .000 .000 BV4 .000 .970 .000 .000 .000 .000 BV3 .000 1.115 .000 .000 .000 .000 BV2 .000 1.140 .000 .000 .000 .000 BV1 .000 1.000 .000 .000 .000 .000 HA4 .000 .000 .991 .000 .000 .000 HA3 .000 .000 .973 .000 .000 .000 HA2 .000 .000 1.332 .000 .000 .000 HA1 .000 .000 1.000 .000 .000 .000 VT4 .000 .000 .000 .976 .000 .000 VT2 .000 .000 .000 1.239 .000 .000 VT1 .000 .000 .000 1.000 .000 .000 VL4 .000 .000 .000 .000 1.123 .000 VL2 .000 .000 .000 .000 .968 .000 VL1 .000 .000 .000 .000 1.000 .000 Standardized Direct Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .456 .135 .200 .345 .110 .000 MT5 .000 .000 .000 .000 .570 .000 MT3 .000 .000 .000 .000 .645 .000 MT2 .000 .000 .000 .000 .680 .000 MT1 .000 .000 .000 .000 .713 .000 GT2 .000 .000 .000 .000 .000 .689 GT1 .000 .000 .000 .000 .000 .825 TT .686 .000 .000 .000 .000 .000 NL .772 .000 .000 .000 .000 .000 PP .695 .000 .000 .000 .000 .000 BV4 .000 .628 .000 .000 .000 .000 BV3 .000 .751 .000 .000 .000 .000 BV2 .000 .711 .000 .000 .000 .000 BV1 .000 .687 .000 .000 .000 .000 HA4 .000 .000 .600 .000 .000 .000 28 PP_NL BV HA VT VL_MT GT. HA3 .000 .000 .603 .000 .000 .000 HA2 .000 .000 .807 .000 .000 .000 HA1 .000 .000 .645 .000 .000 .000 VT4 .000 .000 .000 .762 .000 .000 VT2 .000 .000 .000 .921 .000 .000 VT1 .000 .000 .000 .686 .000 .000 VL4 .000 .000 .000 .000 .763 .000 VL2 .000 .000 .000 .000 .676 .000 VL1 .000 .000 .000 .000 .642 .000 Indirect Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .000 .000 .000 .000 .000 .000 MT5 .000 .000 .000 .000 .000 .000 MT3 .000 .000 .000 .000 .000 .000 MT2 .000 .000 .000 .000 .000 .000 MT1 .000 .000 .000 .000 .000 .000 GT2 .421 .134 .178 .285 .099 .000 GT1 .492 .157 .208 .334 .116 .000 TT .000 .000 .000 .000 .000 .000 NL .000 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .000 .000 .000 .000 .000 BV3 .000 .000 .000 .000 .000 .000 BV2 .000 .000 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .000 .000 .000 .000 HA3 .000 .000 .000 .000 .000 .000 HA2 .000 .000 .000 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .000 .000 .000 VT2 .000 .000 .000 .000 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .000 .000 VL2 .000 .000 .000 .000 .000 .000 VL1 .000 .000 .000 .000 .000 .000 Standardized Indirect Effects (Group number 1 - Default model) PP_NL BV HA VT VL_MT GT. GT. .000 .000 .000 .000 .000 .000 29 PP_NL BV HA VT VL_MT GT. MT5 .000 .000 .000 .000 .000 .000 MT3 .000 .000 .000 .000 .000 .000 MT2 .000 .000 .000 .000 .000 .000 MT1 .000 .000 .000 .000 .000 .000 GT2 .314 .093 .138 .238 .076 .000 GT1 .377 .112 .165 .285 .091 .000 TT .000 .000 .000 .000 .000 .000 NL .000 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .000 .000 .000 .000 .000 BV3 .000 .000 .000 .000 .000 .000 BV2 .000 .000 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .000 .000 .000 .000 HA3 .000 .000 .000 .000 .000 .000 HA2 .000 .000 .000 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .000 .000 .000 VT2 .000 .000 .000 .000 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .000 .000 VL2 .000 .000 .000 .000 .000 .000 VL1 .000 .000 .000 .000 .000 .000 M.I. Par Change BV PP_NL 52.122 .088 HA PP_NL 114.182 .174 e6 PP_NL 43.835 .115 e5 HA 37.748 .103 e23 BV 29.607 .068 e22 HA 40.656 .115 e22 e8 19.872 -.085 e22 e6 16.449 .078 e19 HA 35.591 .101 e16 e4 14.196 -.065 e15 e5 19.061 .090 e14 PP_NL 18.875 .085 e13 e22 15.951 .078 e12 VL_MT 16.100 .060 e12 e23 17.217 .076 30 M.I. Par Change e3 e23 21.776 .074 e1 e14 14.135 -.078 e1 e3 14.488 .062 M.I. Par Change M.I. Par Change MT3 <--- PP_NL 43.835 .299 MT3 <--- HA 16.906 .181 MT3 <--- GT. 22.302 .197 MT3 <--- GT2 23.400 .144 MT3 <--- TT 16.765 .114 MT3 <--- NL 43.979 .163 MT3 <--- PP 24.356 .137 MT3 <--- HA2 16.205 .094 MT2 <--- HA 26.410 .226 MT2 <--- HA4 38.485 .145 MT2 <--- HA2 19.350 .103 MT2 <--- HA1 24.571 .123 MT1 <--- TT 15.288 -.112 MT1 <--- BV1 17.607 -.127 TT <--- BV 79.960 .413 TT <--- HA 34.932 .257 TT <--- VL_MT 38.374 .258 TT <--- MT5 22.834 .135 TT <--- MT3 16.096 .106 TT <--- BV4 47.554 .189 TT <--- BV3 56.256 .214 TT <--- BV2 40.147 .167 TT <--- BV1 36.199 .175 TT <--- HA3 18.683 .102 TT <--- HA1 37.710 .151 TT <--- VL4 50.085 .185 NL <--- HA 58.302 .361 NL <--- MT5 14.009 -.115 NL <--- BV1 17.732 .133 NL <--- HA4 33.647 .146 NL <--- HA3 47.546 .177 NL <--- HA2 50.633 .178 PP <--- VL_MT 14.733 .161 31 M.I. Par Change PP <--- GT. 16.365 .167 PP <--- MT5 23.756 .138 PP <--- MT2 17.249 .110 BV4 <--- HA 25.915 .225 BV4 <--- TT 14.255 .106 BV4 <--- HA4 31.286 .131 BV4 <--- HA2 23.570 .114 BV4 <--- HA1 14.998 .097 BV1 <--- NL 14.420 .087 HA4 <--- MT2 17.560 .129 HA3 <--- PP_NL 18.875 .220 HA3 <--- NL 21.386 .127 HA3 <--- VL1 18.488 -.121 HA2 <--- VL_MT 14.651 -.162 HA2 <--- NL 17.656 .103 HA2 <--- VL4 21.109 -.122 HA1 <--- BV 15.684 .191 HA1 <--- VL_MT 27.457 .228 HA1 <--- MT3 14.925 .106 HA1 <--- MT2 24.970 .138 HA1 <--- MT1 20.802 .118 HA1 <--- VL4 20.610 .124 VT4 <--- MT2 16.688 .094 VL1 <--- HA 15.012 -.174 VL1 <--- HA3 24.703 -.121 Parameter SE SE-SE Mean Bias SE-Bias GT. <--- VL_MT .074 .002 .117 .001 .002 GT. <--- VT .054 .001 .334 .000 .002 GT. <--- HA .069 .002 .207 -.001 .002 GT. <--- BV .097 .002 .155 -.002 .003 GT. <--- PP_NL .066 .001 .496 .004 .002 VL1 <--- VL_MT .000 .000 1.000 .000 .000 VL2 <--- VL_MT .047 .001 .970 .002 .001 VL4 <--- VL_MT .060 .001 1.125 .002 .002 VT1 <--- VT .000 .000 1.000 .000 .000 VT2 <--- VT .077 .002 1.240 .001 .002 VT4 <--- VT .069 .002 .979 .002 .002 HA1 <--- HA .000 .000 1.000 .000 .000 HA2 <--- HA .097 .002 1.334 .003 .003 32 Parameter SE SE-SE Mean Bias SE-Bias HA3 <--- HA .124 .003 .977 .004 .004 HA4 <--- HA .133 .003 .994 .003 .004 BV1 <--- BV .000 .000 1.000 .000 .000 BV2 <--- BV .075 .002 1.143 .003 .002 BV3 <--- BV .086 .002 1.117 .001 .003 BV4 <--- BV .073 .002 .970 .000 .002 PP <--- PP_NL .000 .000 1.000 .000 .000 NL <--- PP_NL .085 .002 1.261 .007 .003 TT <--- PP_NL .073 .002 .983 .005 .002 GT1 <--- GT. .000 .000 1.000 .000 .000 GT2 <--- GT. .057 .001 .856 .001 .002 MT1 <--- VL_MT .079 .002 1.106 .002 .003 MT2 <--- VL_MT .072 .002 .996 .004 .002 MT3 <--- VL_MT .077 .002 .945 .003 .002 MT5 <--- VL_MT .071 .002 .779 .004 .002 Parameter SE SE-SE Mean Bias SE-Bias GT. <--- VL_MT .068 .002 .110 .000 .002 GT. <--- VT .045 .001 .342 -.002 .001 GT. <--- HA .065 .001 .199 -.001 .002 GT. <--- BV .083 .002 .133 -.002 .003 GT. <--- PP_NL .060 .001 .458 .001 .002 VL1 <--- VL_MT .031 .001 .641 .000 .001 VL2 <--- VL_MT .030 .001 .675 .000 .001 VL4 <--- VL_MT .024 .001 .762 -.001 .001 VT1 <--- VT .031 .001 .687 .001 .001 VT2 <--- VT .021 .000 .921 .000 .001 VT4 <--- VT .025 .001 .763 .000 .001 HA1 <--- HA .050 .001 .648 .003 .002 HA2 <--- HA .041 .001 .808 .001 .001 HA3 <--- HA .038 .001 .603 .000 .001 HA4 <--- HA .043 .001 .599 -.001 .001 BV1 <--- BV .030 .001 .686 .000 .001 BV2 <--- BV .029 .001 .711 .000 .001 BV3 <--- BV .026 .001 .750 -.002 .001 BV4 <--- BV .032 .001 .627 -.001 .001 PP <--- PP_NL .032 .001 .693 -.002 .001 NL <--- PP_NL .024 .001 .772 .000 .001 TT <--- PP_NL .029 .001 .686 -.001 .001 GT1 <--- GT. .031 .001 .826 .001 .001 33 Parameter SE SE-SE Mean Bias SE-Bias GT2 <--- GT. .031 .001 .690 .001 .001 MT1 <--- VL_MT .025 .001 .712 -.001 .001 MT2 <--- VL_MT .027 .001 .680 .000 .001 MT3 <--- VL_MT .028 .001 .645 .000 .001 MT5 <--- VL_MT .031 .001 .570 .000 .001 Parameter SE SE-SE Mean Bias SE-Bias VT HA .022 .000 .049 -.001 .001 VL_MT HA .023 .001 .045 .001 .001 VL_MT VT .022 .000 .087 -.001 .001 VL_MT BV .031 .001 .223 .000 .001 VT BV .020 .000 .043 .000 .001 HA BV .026 .001 .173 .000 .001 e1 e2 .022 .001 .159 .001 .001 e14 e15 .048 .001 .207 .000 .002 e12 e13 .064 .001 .128 -.004 .002 e2 e3 .018 .000 .072 -.001 .001 e6 e8 .024 .001 .083 .000 .001 e16 e18 .021 .000 -.083 .002 .001 Parameter SE SE-SE Mean Bias SE-Bias VT HA .050 .001 .111 -.001 .002 VL_MT HA .052 .001 .110 .000 .002 VL_MT VT .046 .001 .199 -.002 .001 VL_MT BV .046 .001 .608 -.002 .001 VT BV .048 .001 .106 .000 .002 HA BV .044 .001 .466 -.002 .001 e1 e2 .036 .001 .313 .003 .001 e14 e15 .054 .001 .295 -.001 .002 e12 e13 .122 .003 .259 -.019 .004 e2 e3 .041 .001 .177 -.002 .001 e6 e8 .045 .001 .165 .001 .001 e16 e18 .065 .001 -.242 .003 .002 Parameter SE SE-SE Mean Bias SE-Bias VL_MT .052 .001 .405 .001 .002 VT .055 .001 .481 .002 .002 HA .069 .002 .417 .006 .002 BV .043 .001 .334 .001 .001 PP_NL .042 .001 .385 -.002 .001 34 Parameter SE SE-SE Mean Bias SE-Bias e27 .036 .001 .227 -.003 .001 e1 .037 .001 .574 -.001 .001 e2 .028 .001 .448 -.001 .001 e3 .027 .001 .365 .000 .001 e9 .041 .001 .535 -.003 .001 e10 .032 .001 .131 -.001 .001 e11 .032 .001 .327 -.002 .001 e12 .066 .001 .570 -.007 .002 e13 .075 .002 .387 -.005 .002 e14 .051 .001 .679 -.001 .002 e15 .056 .001 .715 -.001 .002 e16 .027 .001 .371 -.001 .001 e17 .036 .001 .422 -.002 .001 e18 .028 .001 .319 .000 .001 e19 .032 .001 .479 -.002 .001 e20 .040 .001 .413 .000 .001 e22 .037 .001 .410 -.002 .001 e23 .032 .001 .414 -.001 .001 e24 .031 .001 .208 -.002 .001 e25 .033 .001 .361 -.002 .001 e4 .034 .001 .475 .001 .001 e5 .028 .001 .459 -.002 .001 e6 .032 .001 .501 -.001 .001 e8 .032 .001 .502 -.002 .001 Parameter SE SE-SE Mean Bias SE-Bias GT. .048 .001 .497 .011 .002 MT5 .036 .001 .326 .002 .001 MT3 .036 .001 .416 .000 .001 MT2 .037 .001 .464 .001 .001 MT1 .035 .001 .507 -.001 .001 GT2 .043 .001 .477 .002 .001 GT1 .051 .001 .683 .002 .002 TT .039 .001 .471 .000 .001 NL .038 .001 .597 .001 .001 PP .045 .001 .482 -.001 .001 BV4 .039 .001 .394 .000 .001 BV3 .040 .001 .563 -.002 .001 BV2 .041 .001 .506 .001 .001 BV1 .041 .001 .472 .001 .001 35 Parameter SE SE-SE Mean Bias SE-Bias HA4 .051 .001 .361 .000 .002 HA3 .046 .001 .365 .001 .001 HA2 .066 .001 .655 .004 .002 HA1 .065 .001 .422 .006 .002 VT4 .038 .001 .583 .001 .001 VT2 .038 .001 .848 .000 .001 VT1 .042 .001 .472 .002 .001 VL4 .037 .001 .582 -.001 .001 VL2 .041 .001 .457 .001 .001 VL1 .039 .001 .412 .000 .001 MT 5 MT 3 MT 2 MT 1 GT 2 GT 1 TT NL PP BV 4 BV 3 BV 2 BV 1 HA 4 HA 3 HA 2 HA 1 VT 4 VT 2 VT 1 VL 4 VL 2 VL 1 MT 5 .04 5 MT 3 .04 2 .05 4 MT 2 .03 6 .04 0 .04 6 MT 1 .04 3 .05 0 .04 0 .05 4 GT 2 .03 4 .03 6 .03 5 .03 8 .03 8 GT 1 .03 4 .03 6 .03 3 .03 7 .03 5 .03 8 TT .034 .03 8 .03 4 .03 6 .03 4 .03 3 .04 1 NL .033 .03 6 .03 6 .03 9 .03 2 .03 4 .03 6 .04 1 PP .033 .03 7 .03 4 .03 6 .03 2 .03 2 .03 4 .03 6 .04 1 BV 4 .03 6 .03 8 .03 6 .03 9 .03 6 .03 6 .03 5 .03 4 .03 3 .04 7 BV 3 .03 2 .03 8 .03 7 .03 6 .03 3 .03 1 .03 1 .03 0 .03 1 .03 6 .04 0 BV 2 .03 9 .04 5 .04 1 .04 3 .03 7 .03 9 .04 0 .03 6 .03 5 .04 3 .04 1 .05 3 BV 1 .03 4 .03 9 .03 4 .03 6 .03 4 .03 5 .03 6 .03 3 .03 4 .03 8 .03 3 .04 1 .04 3 HA 4 .03 3 .03 5 .03 7 .03 6 .03 5 .03 4 .03 4 .03 9 .03 7 .03 6 .03 1 .03 7 .03 3 .04 2 HA 3 .03 3 .03 4 .03 5 .03 7 .03 3 .03 5 .03 5 .03 8 .03 4 .03 2 .03 2 .03 7 .03 2 .03 9 .04 1 HA 2 .03 3 .03 4 .03 7 .03 5 .03 2 .03 4 .03 4 .03 8 .03 5 .03 8 .03 1 .03 8 .03 3 .04 3 .03 7 .04 5 HA .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .04 .03 .03 .04 36 MT 5 MT 3 MT 2 MT 1 GT 2 GT 1 TT NL PP BV 4 BV 3 BV 2 BV 1 HA 4 HA 3 HA 2 HA 1 VT 4 VT 2 VT 1 VL 4 VL 2 VL 1 1 3 5 4 2 4 3 6 6 6 6 5 6 7 1 6 9 5 VT 4 .03 2 .03 4 .03 1 .03 6 .03 4 .03 4 .03 1 .03 4 .03 1 .03 0 .03 1 .03 4 .03 2 .03 3 .03 5 .03 2 .03 4 .05 3 VT 2 .03 2 .03 7 .03 3 .03 4 .03 5 .03 6 .03 1 .03 5 .03 4 .03 3 .03 0 .03 6 .03 1 .03 6 .03 6 .03 6 .03 6 .04 8 .05 4 VT 1 .03 1 .03 5 .03 5 .03 4 .03 7 .03 8 .03 3 .03 6 .03 2 .03 2 .03 1 .03 5 .03 1 .03 8 .03 9 .03 8 .03 7 .04 0 .04 7 .04 7 VL 4 .04 0 .04 9 .04 7 .05 1 .04 1 .04 0 .03 8 .03 7 .03 7 .04 2 .04 1 .04 8 .04 2 .03 6 .03 4 .03 5 .03 5 .03 6 .03 6 .03 6 .06 6 VL 2 .03 8 .04 5 .04 4 .04 4 .03 7 .03 5 .03 6 .03 7 .03 5 .04 0 .03 8 .04 3 .03 8 .03 6 .03 3 .03 5 .03 5 .03 4 .03 4 .03 4 .05 6 .05 5 VL 1 .03 7 .04 1 .04 2 .04 5 .03 5 .03 6 .03 6 .03 9 .03 5 .03 9 .03 8 .04 1 .03 6 .03 9 .03 7 .03 8 .03 6 .03 4 .03 4 .03 5 .05 3 .05 2 .05 3 M T5 M T3 M T2 M T1 G T2 G T1 TT N L PP B V4 B V3 B V2 B V1 H A4 H A3 H A2 H A1 V T4 V T2 V T1 V L4 V L2 V L1 M T5 .00 0 M T3 .03 5 .00 0 M T2 .03 3 .03 3 .00 0 M T1 .03 9 .03 2 .03 0 .00 0 GT 2 .04 2 .03 9 .04 1 .04 2 .00 0 GT 1 .04 0 .03 8 .03 7 .04 1 .02 8 .00 0 TT .039 .04 0 .03 8 .03 9 .03 7 .03 7 .0 00 NL .037 .03 5 .03 7 .03 8 .03 3 .03 4 .0 26 .0 00 PP .039 .03 9 .03 7 .04 0 .03 5 .03 3 .0 34 .0 31 .0 00 BV 4 .04 2 .04 0 .03 8 .04 0 .04 1 .04 1 .0 32 .0 33 .0 36 .00 0 BV 3 .03 7 .03 9 .03 9 .03 7 .03 8 .03 6 .0 31 .0 31 .0 36 .03 3 .00 0 BV 2 .04 0 .04 1 .04 0 .03 9 .04 2 .04 2 .0 38 .0 34 .0 38 .03 8 .03 2 .00 0 BV 1 .04 0 .04 3 .03 9 .04 0 .04 1 .04 2 .0 37 .0 32 .0 41 .03 6 .03 7 .03 5 .00 0 H A4 .03 6 .03 5 .03 5 .03 4 .03 6 .03 5 .0 32 .0 32 .0 34 .03 2 .03 3 .03 6 .03 4 .00 0 37 M T5 M T3 M T2 M T1 G T2 G T1 TT N L PP B V4 B V3 B V2 B V1 H A4 H A3 H A2 H A1 V T4 V T2 V T1 V L4 V L2 V L1 H A3 .03 7 .03 5 .03 6 .03 6 .03 7 .03 8 .0 34 .0 32 .0 34 .03 2 .03 5 .03 7 .03 5 .02 7 .00 0 H A2 .03 6 .03 4 .03 6 .03 4 .03 3 .03 4 .0 33 .0 31 .0 34 .03 4 .03 3 .03 7 .03 4 .03 1 .02 8 .00 0 H A1 .03 8 .03 6 .03 4 .03 2 .03 8 .03 6 .0 36 .0 33 .0 38 .03 5 .03 8 .03 5 .04 0 .03 4 .03 1 .02 4 .00 0 VT 4 .04 0 .03 8 .03 5 .03 9 .04 0 .03 6 .0 38 .0 38 .0 38 .03 7 .04 0 .04 1 .04 0 .03 3 .03 8 .03 4 .03 9 .00 0 VT 2 .03 7 .04 1 .03 7 .03 6 .04 0 .03 7 .0 36 .0 36 .0 40 .03 9 .03 7 .04 1 .03 8 .03 5 .03 7 .03 6 .03 9 .02 5 .00 0 VT 1 .03 5 .03 7 .03 7 .03 4 .04 1 .04 0 .0 37 .0 36 .0 36 .03 6 .03 6 .03 7 .03 7 .03 5 .03 7 .03 5 .03 7 .03 3 .03 0 .00 0 VL 4 .03 5 .03 6 .03 4 .03 1 .04 7 .04 4 .0 38 .0 38 .0 41 .04 4 .03 9 .04 0 .04 1 .03 6 .03 5 .03 6 .03 7 .04 0 .03 9 .03 8 .00 0 VL 2 .03 5 .03 6 .03 5 .03 4 .04 4 .03 9 .0 41 .0 39 .0 39 .04 4 .03 9 .04 1 .04 0 .03 7 .03 5 .03 7 .03 8 .03 9 .03 8 .03 7 .03 1 .00 0 VL 1 .03 6 .03 4 .03 2 .03 5 .03 8 .03 8 .0 39 .0 39 .0 38 .04 1 .03 9 .03 9 .04 0 .03 7 .03 6 .03 6 .03 7 .03 7 .03 6 .03 5 .03 1 .02 9 .00 0 M T5 M T3 M T2 M T1 G T2 G T1 T T N L PP B V4 B V3 B V2 B V1 H A4 H A3 H A2 H A1 V T4 V T2 V T1 V L4 V L2 V L1 PP_ NL .00 1 .00 1 .00 1 .00 1 .01 0 .01 3 .0 20 .0 23 .0 32 .00 1 .00 2 .00 1 .00 2 .00 1 .00 1 .00 2 .00 1 .00 2 .00 4 .00 1 .00 1 .00 1 .00 1 BV .002 .00 3 .00 3 .00 3 .00 4 .00 8 .0 01 .0 01 .0 01 .01 3 .02 6 .01 7 .02 7 .00 4 .00 4 .00 6 .00 4 .00 1 .00 4 .00 1 .00 5 .00 3 .00 2 HA .002 .00 2 .00 2 .00 3 .00 7 .01 1 .0 02 .0 02 .0 02 .00 5 .01 0 .00 7 .00 8 .02 3 .02 4 .05 8 .04 4 .00 2 .00 7 .00 1 .00 4 .00 2 .00 2 VT .001 .00 1 .00 1 .00 1 .00 5 .00 8 .0 02 .0 02 .0 02 .00 1 .00 2 .00 1 .00 2 .00 1 .00 1 .00 2 .00 1 .03 8 .05 0 .02 4 .00 2 .00 1 .00 1 VL_ MT .00 9 .01 0 .01 2 .01 3 .00 3 .00 6 .0 01 .0 01 .0 01 .00 3 .00 6 .00 5 .00 5 .00 2 .00 2 .00 4 .00 2 .00 2 .00 4 .00 1 .01 7 .01 4 .01 4 GT. .002 .00 2 .00 3 .00 3 .02 9 .06 8 .0 09 .0 09 .0 09 .00 3 .00 7 .00 5 .00 6 .00 3 .00 3 .00 9 .00 4 .00 6 .01 1 .00 4 .00 4 .00 2 .00 2 PP_NL BV HA VT VL_MT GT. GT. .066 .097 .069 .054 .074 .000 MT5 .000 .000 .000 .000 .071 .000 MT3 .000 .000 .000 .000 .077 .000 MT2 .000 .000 .000 .000 .072 .000 MT1 .000 .000 .000 .000 .079 .000 GT2 .062 .083 .060 .042 .063 .057 GT1 .066 .097 .069 .054 .074 .000 38 PP_NL BV HA VT VL_MT GT. TT .073 .000 .000 .000 .000 .000 NL .085 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .073 .000 .000 .000 .000 BV3 .000 .086 .000 .000 .000 .000 BV2 .000 .075 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .133 .000 .000 .000 HA3 .000 .000 .124 .000 .000 .000 HA2 .000 .000 .097 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .069 .000 .000 VT2 .000 .000 .000 .077 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .060 .000 VL2 .000 .000 .000 .000 .047 .000 VL1 .000 .000 .000 .000 .000 .000 PP_NL BV HA VT VL_MT GT. GT. .060 .083 .065 .045 .068 .000 MT5 .000 .000 .000 .000 .031 .000 MT3 .000 .000 .000 .000 .028 .000 MT2 .000 .000 .000 .000 .027 .000 MT1 .000 .000 .000 .000 .025 .000 GT2 .045 .057 .045 .031 .047 .031 GT1 .048 .068 .053 .041 .056 .031 TT .029 .000 .000 .000 .000 .000 NL .024 .000 .000 .000 .000 .000 PP .032 .000 .000 .000 .000 .000 BV4 .000 .032 .000 .000 .000 .000 BV3 .000 .026 .000 .000 .000 .000 BV2 .000 .029 .000 .000 .000 .000 BV1 .000 .030 .000 .000 .000 .000 HA4 .000 .000 .043 .000 .000 .000 HA3 .000 .000 .038 .000 .000 .000 HA2 .000 .000 .041 .000 .000 .000 HA1 .000 .000 .050 .000 .000 .000 VT4 .000 .000 .000 .025 .000 .000 VT2 .000 .000 .000 .021 .000 .000 VT1 .000 .000 .000 .031 .000 .000 39 PP_NL BV HA VT VL_MT GT. VL4 .000 .000 .000 .000 .024 .000 VL2 .000 .000 .000 .000 .030 .000 VL1 .000 .000 .000 .000 .031 .000 PP_NL BV HA VT VL_MT GT. GT. .066 .097 .069 .054 .074 .000 MT5 .000 .000 .000 .000 .071 .000 MT3 .000 .000 .000 .000 .077 .000 MT2 .000 .000 .000 .000 .072 .000 MT1 .000 .000 .000 .000 .079 .000 GT2 .000 .000 .000 .000 .000 .057 GT1 .000 .000 .000 .000 .000 .000 TT .073 .000 .000 .000 .000 .000 NL .085 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .073 .000 .000 .000 .000 BV3 .000 .086 .000 .000 .000 .000 BV2 .000 .075 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .133 .000 .000 .000 HA3 .000 .000 .124 .000 .000 .000 HA2 .000 .000 .097 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .069 .000 .000 VT2 .000 .000 .000 .077 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .060 .000 VL2 .000 .000 .000 .000 .047 .000 VL1 .000 .000 .000 .000 .000 .000 PP_NL BV HA VT VL_MT GT. GT. .060 .083 .065 .045 .068 .000 MT5 .000 .000 .000 .000 .031 .000 MT3 .000 .000 .000 .000 .028 .000 MT2 .000 .000 .000 .000 .027 .000 MT1 .000 .000 .000 .000 .025 .000 GT2 .000 .000 .000 .000 .000 .031 GT1 .000 .000 .000 .000 .000 .031 TT .029 .000 .000 .000 .000 .000 NL .024 .000 .000 .000 .000 .000 40 PP_NL BV HA VT VL_MT GT. PP .032 .000 .000 .000 .000 .000 BV4 .000 .032 .000 .000 .000 .000 BV3 .000 .026 .000 .000 .000 .000 BV2 .000 .029 .000 .000 .000 .000 BV1 .000 .030 .000 .000 .000 .000 HA4 .000 .000 .043 .000 .000 .000 HA3 .000 .000 .038 .000 .000 .000 HA2 .000 .000 .041 .000 .000 .000 HA1 .000 .000 .050 .000 .000 .000 VT4 .000 .000 .000 .025 .000 .000 VT2 .000 .000 .000 .021 .000 .000 VT1 .000 .000 .000 .031 .000 .000 VL4 .000 .000 .000 .000 .024 .000 VL2 .000 .000 .000 .000 .030 .000 VL1 .000 .000 .000 .000 .031 .000 PP_NL BV HA VT VL_MT GT. GT. .000 .000 .000 .000 .000 .000 MT5 .000 .000 .000 .000 .000 .000 MT3 .000 .000 .000 .000 .000 .000 MT2 .000 .000 .000 .000 .000 .000 MT1 .000 .000 .000 .000 .000 .000 GT2 .062 .083 .060 .042 .063 .000 GT1 .066 .097 .069 .054 .074 .000 TT .000 .000 .000 .000 .000 .000 NL .000 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .000 .000 .000 .000 .000 BV3 .000 .000 .000 .000 .000 .000 BV2 .000 .000 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .000 .000 .000 .000 HA3 .000 .000 .000 .000 .000 .000 HA2 .000 .000 .000 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .000 .000 .000 VT2 .000 .000 .000 .000 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .000 .000 VL2 .000 .000 .000 .000 .000 .000 41 PP_NL BV HA VT VL_MT GT. VL1 .000 .000 .000 .000 .000 .000 PP_NL BV HA VT VL_MT GT. GT. .000 .000 .000 .000 .000 .000 MT5 .000 .000 .000 .000 .000 .000 MT3 .000 .000 .000 .000 .000 .000 MT2 .000 .000 .000 .000 .000 .000 MT1 .000 .000 .000 .000 .000 .000 GT2 .045 .057 .045 .031 .047 .000 GT1 .048 .068 .053 .041 .056 .000 TT .000 .000 .000 .000 .000 .000 NL .000 .000 .000 .000 .000 .000 PP .000 .000 .000 .000 .000 .000 BV4 .000 .000 .000 .000 .000 .000 BV3 .000 .000 .000 .000 .000 .000 BV2 .000 .000 .000 .000 .000 .000 BV1 .000 .000 .000 .000 .000 .000 HA4 .000 .000 .000 .000 .000 .000 HA3 .000 .000 .000 .000 .000 .000 HA2 .000 .000 .000 .000 .000 .000 HA1 .000 .000 .000 .000 .000 .000 VT4 .000 .000 .000 .000 .000 .000 VT2 .000 .000 .000 .000 .000 .000 VT1 .000 .000 .000 .000 .000 .000 VL4 .000 .000 .000 .000 .000 .000 VL2 .000 .000 .000 .000 .000 .000 VL1 .000 .000 .000 .000 .000 .000 Iteration Negative eigenvalues Condition # Smallest eigenvalue Diameter F NTries Ratio 0 e 16 -.938 9999.000 8562.949 0 9999.000 1 e 12 -.212 1.937 5246.778 20 .563 2 e* 2 -.665 1.740 2970.332 4 .663 3 e 0 13966.799 .891 1914.362 5 .761 4 e 1 -.055 .980 1757.130 7 .000 5 e 0 729.118 .745 1364.210 5 .855 6 e 0 444.411 .977 1243.434 1 .712 7 e 0 434.278 .320 1182.090 1 1.086 8 e 0 466.821 .048 1179.506 1 1.067 9 e 0 464.025 .014 1179.460 1 1.019 42 Iteration Negative eigenvalues Condition # Smallest eigenvalue Diameter F NTries Ratio 10 e 0 465.068 .000 1179.460 1 1.001 Iterations Method 0 Method 1 Method 2 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 0 6 0 0 0 7 0 0 0 8 0 4 0 9 0 124 0 10 0 353 0 11 0 267 0 12 0 161 0 13 0 55 0 14 0 23 0 15 0 10 0 16 0 1 0 17 0 2 0 18 0 0 0 19 0 0 0 Total 0 1000 0 |-------------------- 1203.077 |* 1250.040 |** 1297.003 |***** 1343.966 |*********** 1390.929 |*************** 1437.892 |******************* 1484.855 |**************** N = 1000 1531.818 |*********** Mean = 1442.316 1578.781 |****** S. e. = 2.758 1625.744 |** 1672.707 |* 1719.670 |* 1766.633 |* 1813.596 | 43 1860.559 |* |-------------------- |-------------------- 1239.478 |* 1250.005 |*** 1260.532 |******** 1271.060 |**************** 1281.587 |******************** 1292.114 |******************* 1302.641 |**************** N = 1000 1313.168 |********* Mean = 1291.291 1323.695 |****** S. e. = .697 1334.222 |**** 1344.749 |** 1355.276 |* 1365.803 |* 1376.330 |* 1386.857 |* |-------------------- |-------------------- -872.211 |* -700.681 |** -529.151 |**** -357.620 |******** -186.090 |*********** -14.560 |**************** 156.971 |******************** N = 1000 328.501 |****************** Mean = 214.933 500.031 |************** S. e. = 13.011 671.562 |********** 843.092 |****** 1014.622 |**** 1186.152 |* 1357.683 |* 1529.213 |* |-------------------- |-------------------- -77.636 |* 44 -34.303 |* 9.030 |* 52.363 |**** 95.696 |******** 139.030 |************** 182.363 |******************* N = 1000 225.696 |******************** Mean = 219.369 269.029 |*************** S. e. = 2.831 312.362 |*********** 355.695 |******* 399.028 |**** 442.361 |* 485.695 |* 529.028 |* |-------------------- Model NPAR CMIN DF P CMIN/DF Default model 63 1179.460 213 .000 5.537 Saturated model 276 .000 0 Independence model 23 8384.878 253 .000 33.142 Model RMR GFI AGFI PGFI Default model .111 .899 .869 .694 Saturated model .000 1.000 Independence model .237 .363 .305 .332 Model NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI Default model .859 .833 .882 .859 .881 Saturated model 1.000 1.000 1.000 Independence model .000 .000 .000 .000 .000 Model PRATIO PNFI PCFI Default model .842 .723 .742 Saturated model .000 .000 .000 Independence model 1.000 .000 .000 Model NCP LO 90 HI 90 Default model 966.460 862.409 1078.001 Saturated model .000 .000 .000 Independence model 8131.878 7836.104 8433.994 45 Model FMIN F0 LO 90 HI 90 Default model 1.364 1.117 .997 1.246 Saturated model .000 .000 .000 .000 Independence model 9.694 9.401 9.059 9.750 Model RMSEA LO 90 HI 90 PCLOSE Default model .072 .068 .076 .000 Independence model .193 .189 .196 .000 Model AIC BCC BIC CAIC Default model 1305.460 1309.056 1605.585 1668.585 Saturated model 552.000 567.753 1866.832 2142.832 Independence model 8430.878 8432.190 8540.447 8563.447 Model ECVI LO 90 HI 90 MECVI Default model 1.509 1.389 1.638 1.513 Saturated model .638 .638 .638 .656 Independence model 9.747 9.405 10.096 9.748 Model HOELTER .05 HOELTER .01 Default model 182 194 Independence model 31 32 Minimization: .047 Miscellaneous: 1.169 Bootstrap: 4.462 Total: 5.678