Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
TITLE: this is an example of an N=1
first-order autoregressive AR(1) CFA model
with continuous factor indicators
montecarlo:
names are y1-y4;
nobservations = 200;
nreps = 1;
save = ex6.26.dat;
ANALYSIS:
estimator = bayes;
proc = 2;
biter = (2000);
MODEL POPULATION:
f BY y1@1
y2*1
y3*1
y4*1 (&1);
y1-y4*1;
f on f&1*.3;
f*1;
MODEL:
f BY y1@1
y2*1
y3*1
y4*1 (&1);
y1-y4*1;
f on f&1*.3;
f*1;
output:
tech8;
INPUT READING TERMINATED NORMALLY
this is an example of an N=1
first-order autoregressive AR(1) CFA model
with continuous factor indicators
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 200
Number of replications
Requested 1
Completed 1
Value of seed 0
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 2
Observed dependent variables
Continuous
Y1 Y2 Y3 Y4
Continuous latent variables
F F&1
Estimator BAYES
Specifications for Bayesian Estimation
Point estimate MEDIAN
Number of Markov chain Monte Carlo (MCMC) chains 2
Random seed for the first chain 0
Starting value information UNPERTURBED
Algorithm used for Markov chain Monte Carlo GIBBS(PX1)
Convergence criterion 0.500D-01
Maximum number of iterations 50000
K-th iteration used for thinning 1
MODEL FIT INFORMATION
Number of Free Parameters 13
Information Criteria
Deviance (DIC)
Mean 2435.864
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 2435.864 2435.864
0.980 0.000 2435.864 2435.864
0.950 0.000 2435.864 2435.864
0.900 0.000 2435.864 2435.864
0.800 0.000 2435.864 2435.864
0.700 0.000 2435.864 2435.864
0.500 0.000 2435.864 2435.864
0.300 0.000 2435.864 2435.864
0.200 0.000 2435.864 2435.864
0.100 0.000 2435.864 2435.864
0.050 0.000 2435.864 2435.864
0.020 0.000 2435.864 2435.864
0.010 0.000 2435.864 2435.864
Estimated Number of Parameters (pD)
Mean 167.726
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 167.726 167.726
0.980 0.000 167.726 167.726
0.950 0.000 167.726 167.726
0.900 0.000 167.726 167.726
0.800 0.000 167.726 167.726
0.700 0.000 167.726 167.726
0.500 0.000 167.726 167.726
0.300 0.000 167.726 167.726
0.200 0.000 167.726 167.726
0.100 0.000 167.726 167.726
0.050 0.000 167.726 167.726
0.020 0.000 167.726 167.726
0.010 0.000 167.726 167.726
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
F BY
Y1 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Y2 1.000 1.0973 0.0000 0.1248 0.0095 1.000 1.000
Y3 1.000 1.1996 0.0000 0.1431 0.0398 1.000 1.000
Y4 1.000 1.1179 0.0000 0.1390 0.0139 1.000 1.000
F ON
F&1 0.300 0.3100 0.0000 0.0835 0.0001 1.000 1.000
Intercepts
Y1 0.000 0.0827 0.0000 0.1185 0.0068 1.000 0.000
Y2 0.000 0.1665 0.0000 0.1246 0.0277 1.000 0.000
Y3 0.000 0.1409 0.0000 0.1406 0.0199 1.000 0.000
Y4 0.000 0.1139 0.0000 0.1333 0.0130 1.000 0.000
Residual Variances
Y1 1.000 1.0035 0.0000 0.1273 0.0000 1.000 1.000
Y2 1.000 0.8897 0.0000 0.1216 0.0122 1.000 1.000
Y3 1.000 1.0377 0.0000 0.1487 0.0014 1.000 1.000
Y4 1.000 1.1196 0.0000 0.1524 0.0143 1.000 1.000
F 1.000 0.9106 0.0000 0.1819 0.0080 1.000 1.000
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
1 2 3 4
LAMBDA
F F&1
________ ________
Y1 0 0
Y2 5 0
Y3 6 0
Y4 7 0
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 8
Y2 0 9
Y3 0 0 10
Y4 0 0 0 11
ALPHA
F F&1
________ ________
0 0
BETA
F F&1
________ ________
F 0 12
F&1 0 0
PSI
F F&1
________ ________
F 13
F&1 0 0
STARTING VALUES
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
F F&1
________ ________
Y1 1.000 0.000
Y2 1.000 0.000
Y3 1.000 0.000
Y4 1.000 0.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.000 1.000
Y3 0.000 0.000 1.000
Y4 0.000 0.000 0.000 1.000
ALPHA
F F&1
________ ________
0.000 0.000
BETA
F F&1
________ ________
F 0.000 0.300
F&1 0.000 0.000
PSI
F F&1
________ ________
F 1.000
F&1 0.000 1.000
POPULATION VALUES
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
F F&1
________ ________
Y1 1.000 0.000
Y2 1.000 0.000
Y3 1.000 0.000
Y4 1.000 0.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.000 1.000
Y3 0.000 0.000 1.000
Y4 0.000 0.000 0.000 1.000
ALPHA
F F&1
________ ________
0.000 0.000
BETA
F F&1
________ ________
F 0.000 0.300
F&1 0.000 0.000
PSI
F F&1
________ ________
F 1.000
F&1 0.000 1.000
PRIORS FOR ALL PARAMETERS PRIOR MEAN PRIOR VARIANCE PRIOR STD. DEV.
Parameter 1~N(0.000,infinity) 0.0000 infinity infinity
Parameter 2~N(0.000,infinity) 0.0000 infinity infinity
Parameter 3~N(0.000,infinity) 0.0000 infinity infinity
Parameter 4~N(0.000,infinity) 0.0000 infinity infinity
Parameter 5~N(0.000,infinity) 0.0000 infinity infinity
Parameter 6~N(0.000,infinity) 0.0000 infinity infinity
Parameter 7~N(0.000,infinity) 0.0000 infinity infinity
Parameter 8~IG(-1.000,0.000) infinity infinity infinity
Parameter 9~IG(-1.000,0.000) infinity infinity infinity
Parameter 10~IG(-1.000,0.000) infinity infinity infinity
Parameter 11~IG(-1.000,0.000) infinity infinity infinity
Parameter 12~N(0.000,infinity) 0.0000 infinity infinity
Parameter 13~IG(-1.000,0.000) infinity infinity infinity
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR BAYES ESTIMATION
CHAIN BSEED
1 0
2 285380
REPLICATION 1:
POTENTIAL PARAMETER WITH
ITERATION SCALE REDUCTION HIGHEST PSR
100 1.280 6
200 1.313 13
300 1.071 13
400 1.014 10
500 1.031 5
600 1.032 5
700 1.052 6
800 1.012 6
900 1.015 4
1000 1.007 4
1100 1.005 4
1200 1.014 7
1300 1.005 2
1400 1.014 7
1500 1.003 12
1600 1.004 8
1700 1.015 7
1800 1.007 7
1900 1.005 8
2000 1.006 5
SAVEDATA INFORMATION
Order of variables
Y1
Y2
Y3
Y4
Save file
ex6.26.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:24:22
Ending Time: 22:24:22
Elapsed Time: 00:00:00
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