Mplus VERSION 8.8
MUTHEN & MUTHEN
11/27/2022 9:58 AM
OUTPUT SECTIONS
INPUT INSTRUCTIONS
TITLE: Multilevel DSEM model 1 with TINTERVAL
Within level:
- non-random slopes and non-random residual variances
Between level:
- only random means
DATA:
file = MLdata.dat; ! data file
VARIABLE:
NAMES ARE CL TE N RS time person; ! variables names (in the order they appear in the
USEVARIABLES = CL TE; ! which variables to include in the analysis
CLUSTER = person; ! which variable indicates the clustering of the d
LAGGED = CL(1) TE(1); ! create lagged versions of CL and TE (lag 1)
TINTERVAL = time(1); ! which variable indicates the timing of observati
ANALYSIS:
TYPE = TWOLEVEL; ! two-level data
ESTIMATOR = BAYES; ! use Bayesian estimation
PROC = 2; ! use 2 processors
BITER = (5000); ! run at least 5000 iterations (more if needed acc
MODEL:
%WITHIN%
CL ON CL&1; ! autoregression for CL
CL ON TE; ! cross-regression from TE_t -> CL_t
TE ON TE&1; ! autoregression for TE
TE ON CL&1; ! cross-lagged regression CL_t-1 -> TE_t
%BETWEEN%
CL WITH TE; ! person mean on CL covaries with person mean on T
OUTPUT:
TECH1 TECH8 STDYX; ! obtain additional output
PLOT:
TYPE = PLOT3; ! enable plot options
*** WARNING
Input line exceeded 90 characters. Some input may be truncated.
CLUSTER = person; ! which variable indicates the clustering of the da
*** WARNING
Input line exceeded 90 characters. Some input may be truncated.
TINTERVAL = time(1); ! which variable indicates the timing of observatio
*** WARNING
Input line exceeded 90 characters. Some input may be truncated.
BITER = (5000); ! run at least 5000 iterations (more if needed acco
*** WARNING
Input line exceeded 90 characters. Some input may be truncated.
CL WITH TE; ! person mean on CL covaries with person mean on TE
4 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
Multilevel DSEM model 1 with TINTERVAL
Within level:
- non-random slopes and non-random residual variances
Between level:
- only random means
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 19563
Number of dependent variables 2
Number of independent variables 2
Number of continuous latent variables 0
Observed dependent variables
Continuous
CL TE
Observed independent variables
CL&1 TE&1
Variables with special functions
Cluster variable PERSON
Within variables
CL&1 TE&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
Input data file(s)
MLdata.dat
Input data format FREE
SUMMARY OF DATA
Number of clusters 200
Size (s) Cluster ID with Size s
89 186
90 92
92 79 90 147
93 183 23 172
94 15 33 21 28 114 121 163 78 63 24
95 37 200 165 53 124 179 100 162 118 48 75 111 30
96 69 112 81 131 43 175 88 17 192 4 184 38 105 136 135
97 2 182 93 160 139 129 144 67 177 13 45 127 153 133 54
56
98 87 32 159 189 96 91 142 151 193 35 137 180 138 47 72
143 101 22 140 174 31 195 145 122 123 110 104 64 55
198 199 191 42 74 161 5 65 99 152 157 197 20 52 7 80
99 14 36 95 1 11 141 26 83 134 58 49 178 9 130 40 25 171
155 149 84 85 62 181 146 71 39 106 170 125 150 196 176
3 44 98 128 115 50 77 164 168 46 12 57 97 107 120 187
100 173 156 70 10 29 109 113 126 59 132 34 116 169 108 68
41 103 51 18 60 27 185 16 167 73 61 94 8 76 66 86 158
117 82 102 154 19 119 194 148 166 188 190 89 6
COVARIANCE COVERAGE OF DATA
Minimum covariance coverage value 0.100
Number of missing data patterns 4
PROPORTION OF DATA PRESENT
Covariance Coverage
CL TE
________ ________
CL 0.511
TE 0.511 0.511
UNIVARIATE SAMPLE STATISTICS
UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS
Variable/ Mean/ Skewness/ Minimum/ % with Percentiles
Sample Size Variance Kurtosis Maximum Min/Max 20%/60% 40%/80% Median
CL 4.997 -0.530 -5.930 0.01% 3.620 4.680 5.090
9987.000 3.082 1.444 10.480 0.01% 5.490 6.430
TE 14.942 0.046 9.400 0.01% 13.700 14.600 14.900
9987.000 2.323 -0.049 19.900 0.04% 15.300 16.200
THE MODEL ESTIMATION TERMINATED NORMALLY
USE THE FBITERATIONS OPTION TO INCREASE THE NUMBER OF ITERATIONS BY A FACTOR
OF AT LEAST TWO TO CHECK CONVERGENCE AND THAT THE PSR VALUE DOES NOT INCREASE.
MODEL FIT INFORMATION
Number of Free Parameters 11
Information Criteria
Deviance (DIC) 133359.737
Estimated Number of Parameters (pD) 19553.921
MODEL RESULTS
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Within Level
CL ON
CL&1 0.275 0.012 0.000 0.251 0.299 *
TE -0.211 0.011 0.000 -0.233 -0.190 *
TE ON
TE&1 0.103 0.015 0.000 0.075 0.133 *
CL&1 -0.118 0.012 0.000 -0.141 -0.092 *
Residual Variances
CL 1.138 0.017 0.000 1.106 1.172 *
TE 1.013 0.015 0.000 0.984 1.042 *
Between Level
CL WITH
TE -0.766 0.128 0.000 -1.047 -0.542 *
Means
CL 4.996 0.098 0.000 4.800 5.190 *
TE 14.942 0.081 0.000 14.781 15.098 *
Variances
CL 1.841 0.195 0.000 1.510 2.275 *
TE 1.296 0.136 0.000 1.066 1.600 *
STANDARDIZED MODEL RESULTS
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Within Level
CL ON
CL&1 0.275 0.012 0.000 0.251 0.299 *
TE -0.190 0.010 0.000 -0.208 -0.171 *
TE ON
TE&1 0.103 0.015 0.000 0.075 0.133 *
CL&1 -0.131 0.014 0.000 -0.157 -0.103 *
Residual Variances
CL 0.872 0.008 0.000 0.856 0.887 *
TE 0.966 0.005 0.000 0.955 0.975 *
Between Level
CL WITH
TE -0.498 0.055 0.000 -0.600 -0.384 *
Means
CL 3.681 0.205 0.000 3.285 4.097 *
TE 13.119 0.682 0.000 11.834 14.480 *
Variances
CL 1.000 0.000 0.000 1.000 1.000
TE 1.000 0.000 0.000 1.000 1.000
R-SQUARE
Within Level
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
CL 0.128 0.008 0.000 0.113 0.144
TE 0.034 0.005 0.000 0.025 0.045
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR WITHIN
NU
CL TE CL&1 TE&1
________ ________ ________ ________
0 0 0 0
LAMBDA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 0 0 0 0
TE 0 0 0 0
CL&1 0 0 0 0
TE&1 0 0 0 0
THETA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 0
TE 0 0
CL&1 0 0 0
TE&1 0 0 0 0
ALPHA
CL TE CL&1 TE&1
________ ________ ________ ________
0 0 0 0
BETA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 0 1 2 0
TE 0 0 3 4
CL&1 0 0 0 0
TE&1 0 0 0 0
PSI
CL TE CL&1 TE&1
________ ________ ________ ________
CL 5
TE 0 6
CL&1 0 0 0
TE&1 0 0 0 0
PARAMETER SPECIFICATION FOR BETWEEN
NU
CL TE
________ ________
0 0
LAMBDA
CL TE
________ ________
CL 0 0
TE 0 0
THETA
CL TE
________ ________
CL 0
TE 0 0
ALPHA
CL TE
________ ________
7 8
BETA
CL TE
________ ________
CL 0 0
TE 0 0
PSI
CL TE
________ ________
CL 9
TE 10 11
STARTING VALUES FOR WITHIN
NU
CL TE CL&1 TE&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 1.000 0.000 0.000 0.000
TE 0.000 1.000 0.000 0.000
CL&1 0.000 0.000 1.000 0.000
TE&1 0.000 0.000 0.000 1.000
THETA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 0.000
TE 0.000 0.000
CL&1 0.000 0.000 0.000
TE&1 0.000 0.000 0.000 0.000
ALPHA
CL TE CL&1 TE&1
________ ________ ________ ________
0.000 0.000 0.000 0.000
BETA
CL TE CL&1 TE&1
________ ________ ________ ________
CL 0.000 0.000 0.000 0.000
TE 0.000 0.000 0.000 0.000
CL&1 0.000 0.000 0.000 0.000
TE&1 0.000 0.000 0.000 0.000
PSI
CL TE CL&1 TE&1
________ ________ ________ ________
CL 1.541
TE 0.000 1.162
CL&1 0.000 0.000 1.541
TE&1 0.000 0.000 0.000 1.162
STARTING VALUES FOR BETWEEN
NU
CL TE
________ ________
0.000 0.000
LAMBDA
CL TE
________ ________
CL 1.000 0.000
TE 0.000 1.000
THETA
CL TE
________ ________
CL 0.000
TE 0.000 0.000
ALPHA
CL TE
________ ________
4.997 14.942
BETA
CL TE
________ ________
CL 0.000 0.000
TE 0.000 0.000
PSI
CL TE
________ ________
CL 1.541
TE 0.000 1.162
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~IG(-1.000,0.000) infinity infinity infinity
Parameter 6~IG(-1.000,0.000) infinity infinity infinity
Parameter 7~N(0.000,infinity) 0.0000 infinity infinity
Parameter 8~N(0.000,infinity) 0.0000 infinity infinity
Parameter 9~IW(0.000,-3) infinity infinity infinity
Parameter 10~IW(0.000,-3) infinity infinity infinity
Parameter 11~IW(0.000,-3) infinity infinity infinity
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR BAYES ESTIMATION
CHAIN BSEED
1 0
2 285380
POTENTIAL PARAMETER WITH
ITERATION SCALE REDUCTION HIGHEST PSR
100 1.468 4
200 1.046 6
300 1.028 4
400 1.046 4
500 1.016 4
600 1.014 5
700 1.002 11
800 1.006 6
900 1.002 11
1000 1.007 6
1100 1.012 3
1200 1.025 3
1300 1.033 4
1400 1.018 4
1500 1.018 4
1600 1.009 4
1700 1.007 6
1800 1.009 6
1900 1.004 6
2000 1.006 3
2100 1.006 3
2200 1.009 3
2300 1.010 3
2400 1.012 3
2500 1.012 4
2600 1.016 4
2700 1.013 4
2800 1.014 4
2900 1.014 4
3000 1.018 4
3100 1.018 4
3200 1.016 4
3300 1.009 4
3400 1.008 4
3500 1.008 4
3600 1.007 4
3700 1.007 4
3800 1.007 4
3900 1.010 4
4000 1.009 4
4100 1.008 4
4200 1.005 4
4300 1.005 4
4400 1.003 4
4500 1.002 4
4600 1.001 4
4700 1.002 3
4800 1.001 3
4900 1.001 3
5000 1.002 3
PLOT INFORMATION
The following plots are available:
Histograms (sample values)
Scatterplots (sample values)
Between-level histograms (sample values, sample means/variances)
Between-level scatterplots (sample values, sample means/variances)
Time series plots (sample values, ACF, PACF)
Histogram of subjects per time point
Time interval plots
Bayesian posterior parameter distributions
Bayesian posterior parameter trace plots
Bayesian autocorrelation plots
DIAGRAM INFORMATION
Mplus diagrams are currently not available for multilevel analysis.
No diagram output was produced.
Beginning Time: 09:58:54
Ending Time: 09:59:15
Elapsed Time: 00:00:21
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