> library(sem) > cor.mat<-read.moments(names=c("ten1", "ten2", "ten3", "wor1", "wor2", + "wor3", "irthk1", "irthk2", "irthk3", "body1", "body2", "body3")) 1:.7821 2:.5602.9299 4:.5695.6281.9751 7:.1969.2599.2362.6352 11:.2290.2835.3079.4575.7943 16:.2609.3670.3575.4327.4151.6783 22:.0556.0740.0981.2094.2306.2503.6855 29:.0025.0279.0798.2049.2270.2257.4224.6951 37:.0180.0753.0744.1892.2352.2008.4343.4514.6065 46:.1617.1919.2893.1376.1744.1845.0645.0731.0921.4068 56:.2628.3047.4043.1742.2066.2547.1356.1334.1283.1958.7015 67:.2966.3040.3919.1942.1864.2402.1073.0988.0599.2233.3033.5786 79: Read 78 items > cor.mat ten1 ten2 ten3 wor1 wor2 wor3 irthk1 ten1 0.7821 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 ten2 0.5602 0.9299 0.0000 0.0000 0.0000 0.0000 0.0000 ten3 0.5695 0.6281 0.9751 0.0000 0.0000 0.0000 0.0000 wor1 0.1969 0.2599 0.2362 0.6352 0.0000 0.0000 0.0000 wor2 0.2290 0.2835 0.3079 0.4575 0.7943 0.0000 0.0000 wor3 0.2609 0.3670 0.3575 0.4327 0.4151 0.6783 0.0000 irthk1 0.0556 0.0740 0.0981 0.2094 0.2306 0.2503 0.6855 irthk2 0.0025 0.0279 0.0798 0.2049 0.2270 0.2257 0.4224 irthk3 0.0180 0.0753 0.0744 0.1892 0.2352 0.2008 0.4343 body1 0.1617 0.1919 0.2893 0.1376 0.1744 0.1845 0.0645 body2 0.2628 0.3047 0.4043 0.1742 0.2066 0.2547 0.1356 body3 0.2966 0.3040 0.3919 0.1942 0.1864 0.2402 0.1073 irthk2 irthk3 body1 body2 body3 ten1 0.0000 0.0000 0.0000 0.0000 0.0000 ten2 0.0000 0.0000 0.0000 0.0000 0.0000 ten3 0.0000 0.0000 0.0000 0.0000 0.0000 wor1 0.0000 0.0000 0.0000 0.0000 0.0000 wor2 0.0000 0.0000 0.0000 0.0000 0.0000 wor3 0.0000 0.0000 0.0000 0.0000 0.0000 irthk1 0.0000 0.0000 0.0000 0.0000 0.0000 irthk2 0.6951 0.0000 0.0000 0.0000 0.0000 irthk3 0.4514 0.6065 0.0000 0.0000 0.0000 body1 0.0731 0.0921 0.4068 0.0000 0.0000 body2 0.1334 0.1283 0.1958 0.7015 0.0000 body3 0.0988 0.0599 0.2233 0.3033 0.5786 > model.paths<-specify.model() 1: tension -> ten1, lambda11, NA 2: tension -> ten2, lambda12, NA 3: tension -> ten3, lambda13, 1 4: worry -> wor1, lambda21, NA 5: worry -> wor2, lambda22, NA 6: worry -> wor3, lambda23, 1 7: testirt -> irthk1, lambda31, NA 8: testirt -> irthk2, lambda32, NA 9: testirt -> irthk3, lambda33, 1 10: bodysymp -> body1, lambda41, NA 11: bodysymp -> body2, lambda42, NA 12: bodysymp -> body3, lambda43, 1 13: tension <-> worry, phi12, NA
14: tension <-> testirt, phi13, NA 15: tension <-> bodysymp, phi14, NA 16: worry <-> testirt, phi23, NA 17: worry <-> bodysymp, phi24, NA 18: testirt <-> bodysymp, phi34, NA 19: ten1 <-> ten1, ten1.var, NA 20: ten2 <-> ten2, ten2.var, NA 21: ten3 <-> ten3, ten3.var, NA 22: wor1 <-> wor1, wor1.var, NA 23: wor2 <-> wor2, wor2.var, NA 24: wor3 <-> wor3, wor3.var, NA 25: irthk1 <-> irthk1, irthk1.var, NA 26: irthk2 <-> irthk2, irthk2.var, NA 27: irthk3 <-> irthk3, irthk3.var, NA 28: body1 <-> body1, body1.var, NA 29: body2 <-> body2, body2.var, NA 30: body3 <-> body3, body3.var, NA 31: tension <-> tension, NA, 1 32: worry <-> worry, NA, 1 33: testirt <-> testirt, NA, 1 34: bodysymp <-> bodysymp, NA, 1 35: Read 34 records > sem.rtts<-sem(model.paths, cor.mat, 318) > summary(sem.rtts) Model Chisquare = 88.427 Df = 48 Pr(>Chisq) = 0.00034194 Chisquare (null model) = 1766.2 Df = 66 Goodness-of-fit index = 0.95651 Adjusted goodness-of-fit index = 0.92933 RMSEA index = 0.051545 90% CI: (0.034253, 0.068225) Bentler-Bonnett NFI = 0.94993 Tucker-Lewis NNFI = 0.9673 Bentler CFI = 0.97622 SRMR = 0.036438 BIC = -188.15 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -1.40e+00-3.98e-01 8.17e-06 3.89e-03 4.11e-01 1.80e+00 Parameter Estimates Estimate Std Error z value Pr(> z ) lambda11 0.68812 0.044422 15.4906 0.0000e+00 lambda12 0.76487 0.048236 15.8567 0.0000e+00 lambda13 0.84078 0.048017 17.5100 0.0000e+00 lambda21 0.64487 0.040104 16.0797 0.0000e+00 lambda22 0.66488 0.046253 14.3750 0.0000e+00 lambda23 0.66977 0.041568 16.1124 0.0000e+00 lambda31 0.64452 0.041684 15.4619 0.0000e+00 lambda32 0.66880 0.041535 16.1021 0.0000e+00 lambda33 0.67053 0.037832 17.7240 0.0000e+00 lambda41 0.38373 0.036554 10.4976 0.0000e+00 lambda42 0.54429 0.047240 11.5218 0.0000e+00 lambda43 0.55848 0.042318 13.1974 0.0000e+00 phi12 0.55015 0.050853 10.8186 0.0000e+00 phi13 0.11423 0.064882 1.7606 7.8310e-02 phi14 0.77841 0.042329 18.3895 0.0000e+00
phi23 0.49181 0.053226 9.2401 0.0000e+00 phi24 0.59452 0.055420 10.7274 0.0000e+00 phi34 0.28628 0.067921 4.2148 2.4995e-05 ten1.var 0.30858 0.032859 9.3911 0.0000e+00 ten2.var 0.34488 0.038592 8.9367 0.0000e+00 ten3.var 0.26819 0.037779 7.0988 1.2581e-12 wor1.var 0.21935 0.027144 8.0808 6.6613e-16 wor2.var 0.35224 0.036987 9.5233 0.0000e+00 wor3.var 0.22971 0.029387 7.8169 5.3291e-15 irthk1.var 0.27009 0.029031 9.3037 0.0000e+00 irthk2.var 0.24781 0.028509 8.6924 0.0000e+00 irthk3.var 0.15689 0.023736 6.6096 3.8543e-11 body1.var 0.25955 0.024365 10.6526 0.0000e+00 body2.var 0.40525 0.040160 10.0909 0.0000e+00 body3.var 0.26670 0.031939 8.3502 0.0000e+00 lambda11 ten1 <--- tension lambda12 ten2 <--- tension lambda13 ten3 <--- tension lambda21 wor1 <--- worry lambda22 wor2 <--- worry lambda23 wor3 <--- worry lambda31 irthk1 <--- testirt lambda32 irthk2 <--- testirt lambda33 irthk3 <--- testirt lambda41 body1 <--- bodysymp lambda42 body2 <--- bodysymp lambda43 body3 <--- bodysymp phi12 worry <--> tension phi13 testirt <--> tension phi14 bodysymp <--> tension phi23 testirt <--> worry phi24 bodysymp <--> worry phi34 bodysymp <--> testirt ten1.var ten1 <--> ten1 ten2.var ten2 <--> ten2 ten3.var ten3 <--> ten3 wor1.var wor1 <--> wor1 wor2.var wor2 <--> wor2 wor3.var wor3 <--> wor3 irthk1.var irthk1 <--> irthk1 irthk2.var irthk2 <--> irthk2 irthk3.var irthk3 <--> irthk3 body1.var body1 <--> body1 body2.var body2 <--> body2 body3.var body3 <--> body3 Iterations = 36 > mod.indices(sem.rtts) 5 largest modification indices, A matrix: wor3:ten2 ten3:body1 wor1:ten3 wor3:tension ten3:body2 8.722579 8.262219 7.702446 5.653058 5.274448 5 largest modification indices, P matrix: bodysymp:ten3 body3:irthk3 body1:ten3 bodysymp:ten2 wor1:ten3 11.738699 7.627177 7.066307 6.514613 6.264095
> model.paths2<-specify.model() 1: tension -> ten1, lambda11, NA 2: tension -> ten2, lambda12, NA 3: tension -> ten3, lambda13, 1 4: worry -> wor1, lambda21, NA 5: worry -> wor2, lambda22, NA 6: worry -> wor3, lambda23, 1 7: testirt -> irthk1, lambda31, NA 8: testirt -> irthk2, lambda32, NA 9: testirt -> irthk3, lambda33, 1 10: tension <-> worry, phi12, NA 11: tension <-> testirt, phi13, NA 12: worry <-> testirt, phi23, NA 13: ten1 <-> ten1, ten1.var, NA 14: ten2 <-> ten2, ten2.var, NA 15: ten3 <-> ten3, ten3.var, NA 16: wor1 <-> wor1, wor1.var, NA 17: wor2 <-> wor2, wor2.var, NA 18: wor3 <-> wor3, wor3.var, NA 19: irthk1 <-> irthk1, irthk1.var, NA 20: irthk2 <-> irthk2, irthk2.var, NA 21: irthk3 <-> irthk3, irthk3.var, NA 22: tension <-> tension, NA, 1 23: worry <-> worry, NA, 1 24: testirt <-> testirt, NA, 1 25: Read 24 records > #### Run new CFA > sem.rtts2<-sem(model.paths2, cor.mat, 318) Warning message: In sem.mod(model.paths2, cor.mat, 318) : The following observed variables are in the input covariance or raw-moment matrix but do not appear in the model: body1, body2, body3 > summary(sem.rtts2) Model Chisquare = 43.928 Df = 24 Pr(>Chisq) = 0.0077786 Chisquare (null model) = 1387.4 Df = 36 Goodness-of-fit index = 0.97167 Adjusted goodness-of-fit index = 0.94688 RMSEA index = 0.051179 90% CI: (0.025969, 0.074777) Bentler-Bonnett NFI = 0.96834 Tucker-Lewis NNFI = 0.97788 Bentler CFI = 0.98525 SRMR = 0.033690 BIC = -94.361 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -1.2700-0.1910 0.0336 0.0135 0.3650 1.5900 Parameter Estimates Estimate Std Error z value Pr(> z ) lambda11 0.70276 0.044335 15.8512 0.0000e+00 lambda12 0.79562 0.047941 16.5958 0.0000e+00 lambda13 0.79953 0.049356 16.1992 0.0000e+00 lambda21 0.64758 0.040073 16.1598 0.0000e+00
lambda22 0.66725 0.046194 14.4444 0.0000e+00 lambda23 0.66589 0.041715 15.9629 0.0000e+00 lambda31 0.64438 0.041710 15.4490 0.0000e+00 lambda32 0.66765 0.041565 16.0630 0.0000e+00 lambda33 0.67164 0.037842 17.7488 0.0000e+00 phi12 0.54989 0.051015 10.7789 0.0000e+00 phi13 0.10909 0.065032 1.6775 9.3444e-02 phi23 0.49122 0.053271 9.2212 0.0000e+00 ten1.var 0.28822 0.032739 8.8037 0.0000e+00 ten2.var 0.29689 0.038409 7.7296 1.0880e-14 ten3.var 0.33585 0.040652 8.2615 2.2204e-16 wor1.var 0.21584 0.027127 7.9569 1.7764e-15 wor2.var 0.34908 0.036843 9.4747 0.0000e+00 wor3.var 0.23489 0.029661 7.9190 2.4425e-15 irthk1.var 0.27027 0.029093 9.2901 0.0000e+00 irthk2.var 0.24934 0.028570 8.7275 0.0000e+00 irthk3.var 0.15539 0.023821 6.5234 6.8738e-11 lambda11 ten1 <--- tension lambda12 ten2 <--- tension lambda13 ten3 <--- tension lambda21 wor1 <--- worry lambda22 wor2 <--- worry lambda23 wor3 <--- worry lambda31 irthk1 <--- testirt lambda32 irthk2 <--- testirt lambda33 irthk3 <--- testirt phi12 worry <--> tension phi13 testirt <--> tension phi23 testirt <--> worry ten1.var ten1 <--> ten1 ten2.var ten2 <--> ten2 ten3.var ten3 <--> ten3 wor1.var wor1 <--> wor1 wor2.var wor2 <--> wor2 wor3.var wor3 <--> wor3 irthk1.var irthk1 <--> irthk1 irthk2.var irthk2 <--> irthk2 irthk3.var irthk3 <--> irthk3 Iterations = 34