DATE: 8/ 8/2001 TIME: 14:39 L I S R E L 8.30 BY Karl G. Jöreskog & Dag Sörbom This program is published exclusively by Scientific Software International, Inc. 7383 N. Lincoln Avenue, Suite 100 Lincolnwood, IL 60712, U.S.A. Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140 Copyright by Scientific Software International, Inc., 1981-2000 Use of this program is subject to the terms specified in the Universal Copyright Convention. Website: www.ssicentral.com The following lines were read from file E:\ANTI\TRASH.SPL: title: linear conditional antisocial Observed Variables anti1 anti2 anti3 anti4 read1 read2 read3 read4 gen homecog subjid Raw Data from file e:\anti\antiread.dat 3 6 4 5 2.10 2.90 4.50 4.50 1 9 1 Sample size = 221 Latent variables intcept slope Relationships anti1 = 1*intcept 0*slope anti2 = 1*intcept 1*slope anti3 = 1*intcept 2*slope anti4 = 1*intcept 3*slope Equal error variances: anti1 anti2 anti3 anti4 Equation: intcept=gen homecog Equation: slope=gen homecog Let the errors of intcept and slope correlate End of Problem Sample Size = 221 linear conditional antisocial Covariance Matrix to be Analyzed anti1 anti2 anti3 anti4 gen homecog -------- -------- -------- -------- -------- -------- anti1 2.37 anti2 1.16 3.21 anti3 1.22 1.63 3.24 anti4 1.35 2.00 2.24 4.35 gen 0.14 0.18 0.16 0.22 0.25 homecog -0.19 -0.97 -0.87 -1.14 -0.01 6.03 Means anti1 anti2 anti3 anti4 gen homecog -------- -------- -------- -------- -------- -------- 1.49 1.84 1.88 2.07 0.52 9.10 linear conditional antisocial Number of Iterations = 1 LISREL Estimates (Maximum Likelihood) Measurement Equations anti1 = 1.00*intcept, Errorvar.= 1.54 , R² = 0.39 (0.10) 14.83 anti2 = 1.00*intcept + 1.00*slope, Errorvar.= 1.54 , R² = 0.47 (0.10) 14.83 anti3 = 1.00*intcept + 2.00*slope, Errorvar.= 1.54 , R² = 0.56 (0.10) 14.83 anti4 = 1.00*intcept + 3.00*slope, Errorvar.= 1.54 , R² = 0.64 (0.10) 14.83 Structural Equations intcept = 1.82 + 0.57*gen - 0.063*homecog, Errorvar.= 0.86 , R² = 0.11 (0.37) (0.19) (0.038) (0.20) 4.88 3.05 -1.64 4.35 slope = 0.55 + 0.079*gen - 0.045*homecog, Errorvar.= 0.083 , R² = 0.14 (0.17) (0.084) (0.017) (0.043) 3.26 0.94 -2.64 1.95 Error Covariance for slope and intcept = 0.12 (0.070) 1.75 Covariance Matrix of Independent Variables gen homecog -------- -------- gen 0.25 (0.02) 10.49 homecog -0.01 6.03 (0.08) (0.57) -0.08 10.49 Mean Vector of Dependent Variables intcept slope -------- -------- 1.55 0.18 Mean Vector of Independent Variables gen homecog -------- -------- 0.52 9.10 (0.03) (0.17) 15.55 54.98 Goodness of Fit Statistics Degrees of Freedom = 12 Minimum Fit Function Chi-Square = 8.68 (P = 0.73) Normal Theory Weighted Least Squares Chi-Square = 8.90 (P = 0.71) Estimated Non-centrality Parameter (NCP) = 0.0 90 Percent Confidence Interval for NCP = (0.0 ; 7.26) Minimum Fit Function Value = 0.039 Population Discrepancy Function Value (F0) = 0.0 90 Percent Confidence Interval for F0 = (0.0 ; 0.033) Root Mean Square Error of Approximation (RMSEA) = 0.0 90 Percent Confidence Interval for RMSEA = (0.0 ; 0.052) P-Value for Test of Close Fit (RMSEA < 0.05) = 0.94 Expected Cross-Validation Index (ECVI) = 0.16 90 Percent Confidence Interval for ECVI = (0.16 ; 0.20) ECVI for Saturated Model = 0.19 ECVI for Independence Model = 1.36 Chi-Square for Independence Model with 15 Degrees of Freedom = 287.05 Independence AIC = 299.05 Model AIC = 38.90 Saturated AIC = 42.00 Independence CAIC = 325.44 Model CAIC = 104.88 Saturated CAIC = 134.36 Normed Fit Index (NFI) = 0.97 Non-Normed Fit Index (NNFI) = 1.02 Parsimony Normed Fit Index (PNFI) = 0.78 Comparative Fit Index (CFI) = 1.00 Incremental Fit Index (IFI) = 1.01 Relative Fit Index (RFI) = 0.96 Critical N (CN) = 665.31 Root Mean Square Residual (RMR) = 0.13 Standardized RMR = 0.039 Goodness of Fit Index (GFI) = 0.99 Adjusted Goodness of Fit Index (AGFI) = 0.98 Parsimony Goodness of Fit Index (PGFI) = 0.57 The Problem used 8264 Bytes (= 0.0% of Available Workspace) Time used: 0.020 Seconds