CFA分析 总是出现错误，路径图无法显示。 it值 调整也没用。 哪里出了问题？怎么解决？ 请高人帮忙看下！十分感谢 measurement model for test
observed variables: x1-x69
correlation matrix
1.000
.580 1.000
.221 -.018 1.000
.311 -.133 .035 1.000
.127 -.070 .057 .280 1.000
.160 .019 .361 -.001 .367 1.000
.237 .103 .307 .105 .221 .021 1.000
.274 .306 .198 .158 .226 -.105 -.002 1.000
.559 .399 .184 -.033 .179 .271 .000 .041 1.000
-.145 .160 .082 -.354 .159 .442 -.212 -.096 .258 1.000
-.115 -.299 .248 -.038 -.200 .162 .004 .007 -.048 .045 1.000
.039 .146 .315 -.118 .160 .131 .165 .220 -.161 -.173 .107 1.000
-.011 .016 .206 .019 .300 .363 .409 .034 -.113 .180 -.005 .421 1.000
.146 .048 .208 .133 -.012 -.114 -.036 .333 .055 -.218 .257 .456 -.136 1.000
.047 .149 -.085 -.276 .098 .308 .027 .018 .128 .378 .175 .148 .077 .100 1.000
.255 .086 .183 -.129 .116 .261 -.135 .240 .323 .208 .214 .301 -.169 .444 .553 1.000
-.042 -.268 .125 .038 -.104 .093 -.069 -.338 .153 .080 .262 -.125 -.231 -.306 .099 .086 1.000
.029 .053 .066 .019 -.131 -.291 .092 -.014 .015 -.269 -.012 .164 -.083 .198 -.130 -.242 .212 1.000
.285 .118 .170 -.052 -.054 .106 .016 -.234 .594 .396 .120 -.247 -.263 -.114 .161 .291 .640 -.044 1.000
.451 .490 .141 .061 .066 .104 .054 -.087 .389 .323 -.328 -.109 -.025 -.163 .020 .022 .236 .255 .477 1.000
.207 .541 -.084 -.130 .235 -.043 -.158 .324 .155 .357 -.389 .058 -.128 -.018 .104 .045 -.216 .163 .028 .562 1.000
.069 .128 -.056 .271 .047 -.122 -.082 .338 -.283 -.237 -.122 .131 .041 .072 .015 -.186 -.110 .510 -.514 .280 .415 1.000
.062 .268 -.188 -.050 .066 -.206 -.154 .555 .082 .001 -.150 .010 -.241 .045 .293 .155 -.134 .060 .019 .017 .410 .163 1.000
.127 .165 .079 -.129 -.057 -.093 .045 .421 .000 -.304 -.119 .312 .031 .059 .329 .214 .128 .198 -.021 -.044 -.027 .174 .567 1.000
-.062 -.102 .415 .130 -.098 -.060 .040 -.125 .029 .347 .019 .016 .225 .145 .113 .064 .119 .078 .292 .301 .014 -.013 -.199 -.042 1.000
.095 .227 .032 -.029 -.433 -.084 -.094 -.239 .105 -.080 .155 .194 -.006 -.104 -.041 -.041 .384 .496 .237 .215 -.021 .102 -.070 .216 .165 1.000
.083 .067 .095 .065 -.029 -.002 -.106 .022 .101 .242 -.014 .086 .188 .007 .087 .029 .017 .350 .179 .552 .381 .340 .182 .116 .405 .277 1.000
-.049 .186 .109 -.071 -.189 -.149 -.026 .031 .025 .302 -.113 .178 .211 .118 .018 -.034 .086 .262 .292 .575 .295 .178 .149 .122 .570 .158 .698 1.000
-.332 -.264 .134 -.301 -.044 -.014 .004 -.307 -.088 .272 .014 .108 .242 -.287 -.004 -.097 .483 .202 .329 .191 -.107 -.133 -.197 .220 .497 .394 .308 .466 1.000
.129 .232 .303 -.037 -.126 -.188 .313 -.083 -.079 -.011 -.007 .220 .181 -.040 -.261 -.157 .201 .196 .326 .366 .063 -.134 -.285 -.024 .369 .380 .109 .355 .408 1.000
.
sample size: 500
Latent Variables: com wis rug sop tre lik sin exc tra ben
Relations
x1-x9=com
x10-x16=wis
x17-x25=rug
x26-x33=sop
x34-x40=tre
x41-x47=lik
x48-x50=sin
x51-x56=exc
x57-x59=tra
x60-x69=ben
Options: nd=3 it=100 ad=off
Lisrel Output
 ath Diagram
End of problem
W_A_R_N_I_N_G: Matrix to be analyzed is not positive definite,
ridge option taken with ridge constant = 0.010
measurement model for test W_A_R_N_I_N_G: The solution has not converged after 100 iterations.
The following solution is preliminary and is provided only
for the purpose of tracing the source of the problem.
Setting IT>100 may solve the problem.
Goodness of Fit Statistics
Degrees of Freedom = 2232
Minimum Fit Function Chi-Square = 79691.980 (P = 0.0)
Normal Theory Weighted Least Squares Chi-Square = 45236.891 (P = 0.0)
Estimated Non-centrality Parameter (NCP) = 43004.891
90 Percent Confidence Interval for NCP = (42315.658 ; 43699.492)
Minimum Fit Function Value = http://bbs.pinggu.org/159.703
Population Discrepancy Function Value (F0) = 86.182
90 Percent Confidence Interval for F0 = (84.801 ; 87.574)
Root Mean Square Error of Approximation (RMSEA) = 0.196
90 Percent Confidence Interval for RMSEA = (0.195 ; 0.198)
P-Value for Test of Close Fit (RMSEA < 0.05) = 0.000
Expected Cross-Validation Index (ECVI) = 91.389
90 Percent Confidence Interval for ECVI = (90.007 ; 92.781)
ECVI for Saturated Model = 9.679
ECVI for Independence Model = 124.135
Chi-Square for Independence Model with 2346 Degrees of Freedom = 61805.444
Independence AIC = 61943.444
Model AIC = 45602.891
Saturated AIC = 4830.000
Independence CAIC = 62303.252
Model CAIC = 46557.164
Saturated CAIC = 17423.279
Normed Fit Index (NFI) = -0.289
Non-Normed Fit Index (NNFI) = -0.369
Parsimony Normed Fit Index (PNFI) = -0.275
Comparative Fit Index (CFI) = 0.0
Incremental Fit Index (IFI) = -0.300
Relative Fit Index (RFI) = -0.355
Critical N (CN) = 15.968
Root Mean Square Residual (RMR) = 0.192
Standardized RMR = 0.189
Goodness of Fit Index (GFI) = 0.276
Adjusted Goodness of Fit Index (AGFI) = 0.217
Parsimony Goodness of Fit Index (PGFI) = 0.255 Modification Indices cannot be Computed Because Iterations have not Converged Time used: 2.309 Seconds | 
