[求助]初学者，lisrel错误，怎么解决？
<p>CFA分析</p><p>总是出现错误，路径图无法显示。</p><p>it值 调整也没用。</p><p>哪里出了问题？怎么解决？</p><p>请高人帮忙看下！十分感谢</p><p> measurement model for test<br/> observed variables: x1-x69<br/> <br/> correlation matrix<br/> 1.000<br/> .580 1.000<br/> .221 -.018 1.000<br/> .311 -.133 .035 1.000<br/> .127 -.070 .057 .280 1.000<br/> .160 .019 .361 -.001 .367 1.000<br/> .237 .103 .307 .105 .221 .021 1.000<br/> .274 .306 .198 .158 .226 -.105 -.002 1.000<br/> .559 .399 .184 -.033 .179 .271 .000 .041 1.000<br/> -.145 .160 .082 -.354 .159 .442 -.212 -.096 .258 1.000<br/> -.115 -.299 .248 -.038 -.200 .162 .004 .007 -.048 .045 1.000<br/> .039 .146 .315 -.118 .160 .131 .165 .220 -.161 -.173 .107 1.000<br/> -.011 .016 .206 .019 .300 .363 .409 .034 -.113 .180 -.005 .421 1.000<br/> .146 .048 .208 .133 -.012 -.114 -.036 .333 .055 -.218 .257 .456 -.136 1.000<br/> .047 .149 -.085 -.276 .098 .308 .027 .018 .128 .378 .175 .148 .077 .100 1.000<br/> .255 .086 .183 -.129 .116 .261 -.135 .240 .323 .208 .214 .301 -.169 .444 .553 1.000<br/> -.042 -.268 .125 .038 -.104 .093 -.069 -.338 .153 .080 .262 -.125 -.231 -.306 .099 .086 1.000<br/> .029 .053 .066 .019 -.131 -.291 .092 -.014 .015 -.269 -.012 .164 -.083 .198 -.130 -.242 .212 1.000<br/> .285 .118 .170 -.052 -.054 .106 .016 -.234 .594 .396 .120 -.247 -.263 -.114 .161 .291 .640 -.044 1.000<br/> .451 .490 .141 .061 .066 .104 .054 -.087 .389 .323 -.328 -.109 -.025 -.163 .020 .022 .236 .255 .477 1.000<br/> .207 .541 -.084 -.130 .235 -.043 -.158 .324 .155 .357 -.389 .058 -.128 -.018 .104 .045 -.216 .163 .028 .562 1.000<br/> .069 .128 -.056 .271 .047 -.122 -.082 .338 -.283 -.237 -.122 .131 .041 .072 .015 -.186 -.110 .510 -.514 .280 .415 1.000<br/> .062 .268 -.188 -.050 .066 -.206 -.154 .555 .082 .001 -.150 .010 -.241 .045 .293 .155 -.134 .060 .019 .017 .410 .163 1.000<br/> .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<br/> -.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<br/> .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<br/> .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<br/> -.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<br/> -.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<br/> .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<br/> . <br/> sample size: 500<br/> <br/> Latent Variables: com wis rug sop tre lik sin exc tra ben<br/> Relations<br/> x1-x9=com<br/> x10-x16=wis<br/> x17-x25=rug<br/> x26-x33=sop<br/> x34-x40=tre<br/> x41-x47=lik<br/> x48-x50=sin<br/> x51-x56=exc<br/> x57-x59=tra<br/> x60-x69=ben<br/> <br/> Options: nd=3 it=100 ad=off<br/> Lisrel Output<br/> <br/> Path Diagram<br/> End of problem</p><p><br/><strong>W_A_R_N_I_N_G: Matrix to be analyzed is not positive definite,<br/> ridge option taken with ridge constant = 0.010</strong></p><p> measurement model for test </p><p><strong> W_A_R_N_I_N_G: The solution has not converged after 100 iterations.<br/> The following solution is preliminary and is provided only<br/> for the purpose of tracing the source of the problem.<br/> Setting IT>100 may solve the problem.</strong></p><p> </p><p><br/> Goodness of Fit Statistics</p><p> Degrees of Freedom = 2232<br/> Minimum Fit Function Chi-Square = 79691.980 (P = 0.0)<br/> Normal Theory Weighted Least Squares Chi-Square = 45236.891 (P = 0.0)<br/> Estimated Non-centrality Parameter (NCP) = 43004.891<br/> 90 Percent Confidence Interval for NCP = (42315.658 ; 43699.492)<br/> <br/> Minimum Fit Function Value = http://bbs.pinggu.org/159.703<br/> Population Discrepancy Function Value (F0) = 86.182<br/> 90 Percent Confidence Interval for F0 = (84.801 ; 87.574)<br/> Root Mean Square Error of Approximation (RMSEA) = 0.196<br/> 90 Percent Confidence Interval for RMSEA = (0.195 ; 0.198)<br/> P-Value for Test of Close Fit (RMSEA < 0.05) = 0.000<br/> <br/> Expected Cross-Validation Index (ECVI) = 91.389<br/> 90 Percent Confidence Interval for ECVI = (90.007 ; 92.781)<br/> ECVI for Saturated Model = 9.679<br/> ECVI for Independence Model = 124.135<br/> <br/> Chi-Square for Independence Model with 2346 Degrees of Freedom = 61805.444<br/> Independence AIC = 61943.444<br/> Model AIC = 45602.891<br/> Saturated AIC = 4830.000<br/> Independence CAIC = 62303.252<br/> Model CAIC = 46557.164<br/> Saturated CAIC = 17423.279<br/> <br/> Normed Fit Index (NFI) = -0.289<br/> Non-Normed Fit Index (NNFI) = -0.369<br/> Parsimony Normed Fit Index (PNFI) = -0.275<br/> Comparative Fit Index (CFI) = 0.0<br/> Incremental Fit Index (IFI) = -0.300<br/> Relative Fit Index (RFI) = -0.355<br/> <br/> Critical N (CN) = 15.968<br/> <br/> <br/> Root Mean Square Residual (RMR) = 0.192<br/> Standardized RMR = 0.189<br/> Goodness of Fit Index (GFI) = 0.276<br/> Adjusted Goodness of Fit Index (AGFI) = 0.217<br/> Parsimony Goodness of Fit Index (PGFI) = 0.255</p><p> Modification Indices cannot be Computed Because Iterations have not Converged</p><p> Time used: 2.309 Seconds</p> <p>可以尝试两种方法：</p><p>1、如果你的原始数据有缺乏值，在处理缺失值时用EM算法，不要用pairwise法</p><p>2、将迭代次数调大一点，比如 IT=20000</p> <p>根本原因是输入矩阵不正定，具体解决方法要按具体情况分析：</p><p>1、可能数据输入有误，出现极端数据。解决方法是检查数据。</p><p>2、问卷设计不合理，变量关系混乱。解决方法是重新设计问卷，合并问题。</p><p>3、问卷数据质量太差，被调查人回答问题太随意，极端值多。解决方法，检查问卷，删除不合格问卷。</p><p>4、数据变量间高度线性相关。解决方法是检查数据，删除高度相关问卷。</p><p>5、程序估计初始值不合理。解决方法是自行输入初始值。</p> 问题解决了，太感谢了。 TI<br /> DA NI=8 NO=160 MA=CM<br /> LA<br /> ld sd zcfz ldzczz zzczz zcbc xsml xsjl<br /> CM FI='C:\test.cov' SY<br /> MO NX=8 NK=3 TD=SY<br /> LK<br /> yl yy cz<br /> FR LX(1,3) LX(2,3) LX(3,3) LX(4,2) LX(5,2) LX(6,1) LX(7,1) LX(8,1)<br /> PD<br /> OU IT=50000 AD=OFF<br /> <br /> TI <br /> <br /> Number of Input Variables 8<br /> Number of Y - Variables 0<br /> Number of X - Variables 8<br /> Number of ETA - Variables 0<br /> Number of KSI - Variables 3<br /> Number of Observations 160<br /> <br /> <br /> W_A_R_N_I_N_G: Matrix to be analyzed is not positive definite,<br /> ridge option taken with ridge constant = 0.001<br /> <br /> TI <br /> <br /> Covariance Matrix <br /> <br /> ld sd zcfz ldzczz zzczz zcbc <br /> -------- -------- -------- -------- -------- --------<br /> ld 1.00<br /> sd 1.00 1.00<br /> zcfz -0.73 -0.73 1.00<br /> ldzczz -0.58 -0.58 0.97 1.00<br /> zzczz -0.29 -0.29 0.42 0.36 1.00<br /> zcbc 0.86 0.86 -0.55 -0.43 0.17 1.00<br /> xsml 0.33 0.33 -0.60 -0.57 -0.58 0.01<br /> xsjl 0.35 0.35 -0.53 -0.47 -0.84 -0.09<br /> <br /> Covariance Matrix <br /> <br /> xsml xsjl <br /> -------- --------<br /> xsml 1.00<br /> xsjl 0.77 1.00<br /> <br /> <br /> TI <br /> <br /> Parameter Specifications<br /> <br /> LAMBDA-X <br /> <br /> yl yy cz<br /> -------- -------- --------<br /> ld 0 0 1<br /> sd 0 0 2<br /> zcfz 0 0 3<br /> ldzczz 0 4 0<br /> zzczz 0 5 0<br /> zcbc 6 0 0<br /> xsml 7 0 0<br /> xsjl 8 0 0<br /> <br /> PHI <br /> <br /> yl yy cz<br /> -------- -------- --------<br /> yl 0<br /> yy 9 0<br /> cz 10 11 0<br /> <br /> THETA-DELTA <br /> <br /> ld sd zcfz ldzczz zzczz zcbc<br /> -------- -------- -------- -------- -------- --------<br /> 12 13 14 15 16 17<br /> <br /> THETA-DELTA <br /> <br /> xsml xsjl<br /> -------- --------<br /> 18 19<br /> <br /> <br /> <br /> TI <br /> <br /> W_A_R_N_I_N_G: The solution has not converged after**** iterations.<br /> The following solution is preliminary and is provided only<br /> for the purpose of tracing the source of the problem.<br /> Setting IT>*** may solve the problem.<br /> <br /> LISREL Estimates(Intermediate Solution) <br /> <br /> LAMBDA-X <br /> <br /> yl yy cz <br /> -------- -------- --------<br /> ld - - - - 1.01<br /> sd - - - - 1.01<br /> zcfz - - - - -0.74<br /> ldzczz - - 0.28 - -<br /> zzczz - - 1.27 - -<br /> zcbc 0.21 - - - -<br /> xsml 0.01 - - - -<br /> xsjl 0.04 - - - -<br /> <br /> PHI <br /> <br /> yl yy cz <br /> -------- -------- --------<br /> yl 1.00<br /> yy 0.29 1.00<br /> cz 4.45 -0.16 1.00<br /> <br /> THETA-DELTA <br /> <br /> ld sd zcfz ldzczz zzczz zcbc <br /> -------- -------- -------- -------- -------- --------<br /> 0.00 0.00 0.46 0.92 -0.61 0.96<br /> <br /> THETA-DELTA <br /> <br /> xsml xsjl <br /> -------- --------<br /> 1.00 1.00<br /> <br /> LX was written to file C:\DUMP<br /> <br /> PH was written to file C:\DUMP<br /> <br /> TD was written to file C:\DUMP<br /> <br /> <br /> Goodness of Fit Statistics<br /> <br /> Degrees of Freedom = 17<br /> Minimum Fit Function Chi-Square = 1064.47 (P = 0.0)<br /> Normal Theory Weighted Least Squares Chi-Square = 516.77 (P = 0.0)<br /> Estimated Non-centrality Parameter (NCP) = 499.77<br /> 90 Percent Confidence Interval for NCP = (429.27 ; 577.69)<br /> <br /> Minimum Fit Function Value = http://bbs.pinggu.org/6.69<br /> Population Discrepancy Function Value (F0) = 3.14<br /> 90 Percent Confidence Interval for F0 = (2.70 ; 3.63)<br /> Root Mean Square Error of Approximation (RMSEA) = 0.43<br /> 90 Percent Confidence Interval for RMSEA = (0.40 ; 0.46)<br /> P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00<br /> <br /> Expected Cross-Validation Index (ECVI) = 3.49<br /> 90 Percent Confidence Interval for ECVI = (3.05 ; 3.98)<br /> ECVI for Saturated Model = 0.45<br /> ECVI for Independence Model = 9.53<br /> <br /> Chi-Square for Independence Model with 28 Degrees of Freedom = 1498.67<br /> Independence AIC = 1514.67<br /> Model AIC = 554.77<br /> Saturated AIC = 72.00<br /> Independence CAIC = 1547.27<br /> Model CAIC = 632.20<br /> Saturated CAIC = 218.71<br /> <br /> Normed Fit Index (NFI) = 0.29<br /> Non-Normed Fit Index (NNFI) = -0.17<br /> Parsimony Normed Fit Index (PNFI) = 0.18<br /> Comparative Fit Index (CFI) = 0.29<br /> Incremental Fit Index (IFI) = 0.29<br /> Relative Fit Index (RFI) = -0.17<br /> <br /> Critical N (CN) = 5.99<br /> <br /> <br /> Root Mean Square Residual (RMR) = 0.36<br /> Standardized RMR = 0.36<br /> Goodness of Fit Index (GFI) = 0.55<br /> Adjusted Goodness of Fit Index (AGFI) = 0.050<br /> Parsimony Goodness of Fit Index (PGFI) = 0.26<br /> <br /> Modification Indices cannot be Computed Because Iterations have not Converged<br /> <br /> Time used: 41.688 Seconds 望高手指点下上面的问题，不知为什么，CFA运行老出问题！ 路過 學習一下页:
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