基于mplus的二参数项目反应理论 2016-11-03 [url=]评价者[/url]

INPUT INSTRUCTIONS
TITLE: this is an example of a CFA with categorical factor indicators
DATA: FILE IS ex5.2.dat;
VARIABLE:
NAMES ARE u1-u6;
CATEGORICAL ARE u1-u6;
MODEL: f1 BY u1-u3;
f2 BY u4-u6;
this is an example of a CFA withcategorical factor indicators
SUMMARY OF ANALYSIS
Number of groups
1Number of observations
500Number of dependent variables
6Number of independent variables
0Number of continuous latent variables
2Observed dependent variables
Binary and ordered categorical (ordinal) U1 U2 U3 U4 U5 U6
Continuous latent variables F1 F2
Estimator
WLSMVMaximum number of iterations
1000Convergence criterion
0.500D-04Maximum number of steepest descent iterations
20Parameterization
DELTAInput data file(s)ex5.2.dat
Input data format
FREEUNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES
U1 Category 1 0.504 252.000
Category 2 0.496 248.000
U2
Category 1 0.506 253.000
Category 2 0.494 247.000
U3
Category 1 0.496 248.000
Category 2 0.504 252.000
U4
Category 1 0.524 262.000
Category 2 0.476 238.000
U5 Category 1 0.508 254.000
Category 2 0.492 246.000
U6 Category 1 0.510 255.000
Category 2 0.490 245.000
THE MODEL ESTIMATION TERMINATED NORMALLYTESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 5.482*
Degrees of Freedom 8
P-Value 0.7051*
The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV
cannot be used for chi-square difference testing in the regular way.
MLM, MLR and WLSM chi-square difference testing is described on the Mplus website.
MLMV, WLSMV, and ULSMV difference testing is done using the DIFFTEST option.
Chi-Square Test of Model Fit for the Baseline Model Value 2808.627
Degrees of Freedom 15
P-Value 0.0000
CFI/TLI CFI 1.000 TLI 1.002
Number of Free Parameters 13
RMSEA (Root Mean Square Error Of Approximation) Estimate
0.000WRMR (Weighted Root Mean Square Residual) Value
0.342
MODEL RESULTS Two-Tailed Estimate S.E.Est./S.E. P-Value
F1 BY U1
1.000 0.000 999.000 999.000
U2 1.067 0.043 24.661 0.000
U3 1.001 0.039 25.913 0.000
F2 BY U4 1.000 0.000 999.000 999.000
U5 1.109 0.054 20.482 0.000
U6 1.030 0.047 21.988 0.000
F2 WITH F1 -0.021 0.049 -0.432 0.666
Thresholds U1$1 0.010 0.056 0.179 0.858
U2$1 0.015 0.056 0.268 0.788
U3$1 -0.010 0.056 -0.179 0.858
U4$1 0.060 0.056 1.073 0.283
U5$1 0.020 0.056 0.358 0.721
U6$1 0.025 0.056 0.447 0.655
Variances F1 0.800 0.046 17.439 0.000
F2 0.736 0.052 14.099 0.000
R-SQUARE
Observed Residual
Variable Estimat Variance
U1 0.800 0.200
U2 0.912 0.088
U3 0.802 0.198
U4 0.736 0.264
U5 0.906 0.094
U6 0.781 0.219
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.200E-01 (ratio of smallest to largest eigenvalue)
Beginning Time:18:12:40
Ending Time:18:12:40
Elapsed Time:00:00:00

转自评价者
我看了一下代码,其实就是做CFA.