Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
Title: N=1 bivariate cross-lagged analysis
MONTECARLO: NAMES ARE y1 y2;
NOBS = 100;
NREP = 1;
lagged = y1(1) y2(1);
save = ex6.25.dat;
ANALYSIS:
estimator=bayes;
biter=(500);
proc=2;
MODEL MONTECARLO:
y1 on y1&1*.2 y2&1*-.3;
y2 on y2&1*.1 y1&1*.3;
y1-y2*1;
MODEL:
y1 on y1&1*.2 y2&1*-.3;
y2 on y2&1*.1 y1&1*.3;
y1-y2*1;
output:
tech8;
INPUT READING TERMINATED NORMALLY
N=1 bivariate cross-lagged analysis
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 100
Number of replications
Requested 1
Completed 1
Value of seed 0
Number of dependent variables 2
Number of independent variables 2
Number of continuous latent variables 0
Observed dependent variables
Continuous
Y1 Y2
Observed independent variables
Y1&1 Y2&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 9
Information Criteria
Deviance (DIC)
Mean 590.927
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 590.927 590.927
0.980 0.000 590.927 590.927
0.950 0.000 590.927 590.927
0.900 0.000 590.927 590.927
0.800 0.000 590.927 590.927
0.700 0.000 590.927 590.927
0.500 0.000 590.927 590.927
0.300 0.000 590.927 590.927
0.200 0.000 590.927 590.927
0.100 0.000 590.927 590.927
0.050 0.000 590.927 590.927
0.020 0.000 590.927 590.927
0.010 0.000 590.927 590.927
Estimated Number of Parameters (pD)
Mean 8.792
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 8.792 8.792
0.980 0.000 8.792 8.792
0.950 0.000 8.792 8.792
0.900 0.000 8.792 8.792
0.800 0.000 8.792 8.792
0.700 0.000 8.792 8.792
0.500 0.000 8.792 8.792
0.300 0.000 8.792 8.792
0.200 0.000 8.792 8.792
0.100 0.000 8.792 8.792
0.050 0.000 8.792 8.792
0.020 0.000 8.792 8.792
0.010 0.000 8.792 8.792
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Y1 ON
Y1&1 0.200 0.0118 0.0000 0.1104 0.0354 1.000 0.000
Y2&1 -0.300 -0.2370 0.0000 0.1064 0.0040 1.000 1.000
Y2 ON
Y2&1 0.100 -0.0187 0.0000 0.0976 0.0141 1.000 0.000
Y1&1 0.300 0.3439 0.0000 0.0962 0.0019 1.000 1.000
Y2 WITH
Y1 0.000 -0.0062 0.0000 0.1188 0.0000 1.000 0.000
Intercepts
Y1 0.000 -0.0190 0.0000 0.1100 0.0004 1.000 0.000
Y2 0.000 0.1111 0.0000 0.0995 0.0123 1.000 0.000
Residual Variances
Y1 1.000 1.2014 0.0000 0.1979 0.0406 1.000 1.000
Y2 1.000 1.0177 0.0000 0.1582 0.0003 1.000 1.000
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION
NU
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
0 0 0 0
LAMBDA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0 0 0 0
Y2 0 0 0 0
Y1&1 0 0 0 0
Y2&1 0 0 0 0
THETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0
Y2 0 0
Y1&1 0 0 0
Y2&1 0 0 0 0
ALPHA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
1 2 0 0
BETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0 0 3 4
Y2 0 0 5 6
Y1&1 0 0 0 0
Y2&1 0 0 0 0
PSI
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 7
Y2 8 9
Y1&1 0 0 0
Y2&1 0 0 0 0
STARTING VALUES
NU
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 1.000 0.000 0.000 0.000
Y2 0.000 1.000 0.000 0.000
Y1&1 0.000 0.000 1.000 0.000
Y2&1 0.000 0.000 0.000 1.000
THETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0.000
Y2 0.000 0.000
Y1&1 0.000 0.000 0.000
Y2&1 0.000 0.000 0.000 0.000
ALPHA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
BETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0.000 0.000 0.200 -0.300
Y2 0.000 0.000 0.300 0.100
Y1&1 0.000 0.000 0.000 0.000
Y2&1 0.000 0.000 0.000 0.000
PSI
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 1.000
Y2 0.000 1.000
Y1&1 0.000 0.000 0.500
Y2&1 0.000 0.000 0.000 0.500
POPULATION VALUES
NU
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 1.000 0.000 0.000 0.000
Y2 0.000 1.000 0.000 0.000
Y1&1 0.000 0.000 1.000 0.000
Y2&1 0.000 0.000 0.000 1.000
THETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0.000
Y2 0.000 0.000
Y1&1 0.000 0.000 0.000
Y2&1 0.000 0.000 0.000 0.000
ALPHA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
BETA
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 0.000 0.000 0.200 -0.300
Y2 0.000 0.000 0.300 0.100
Y1&1 0.000 0.000 0.000 0.000
Y2&1 0.000 0.000 0.000 0.000
PSI
Y1 Y2 Y1&1 Y2&1
________ ________ ________ ________
Y1 1.000
Y2 0.000 1.000
Y1&1 0.000 0.000 1.000
Y2&1 0.000 0.000 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~IW(0.000,-3) infinity infinity infinity
Parameter 8~IW(0.000,-3) infinity infinity infinity
Parameter 9~IW(0.000,-3) 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 1.031 2
200 1.001 8
300 1.000 1
400 1.007 2
500 1.001 3
SAVEDATA INFORMATION
Order of variables
Y1
Y2
Y1&1
Y2&1
Save file
ex6.25.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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