Mplus VERSION 8.6
MUTHEN & MUTHEN
05/18/2021 9:38 AM
OUTPUT SECTIONS
INPUT INSTRUCTIONS
TITLE: Multilevel model for decomposition into
within and between variance
DATA: file is ChapterData1.dat;
VARIABLE:
NAMES = ID prepost TimeHours U2P PA NA PEx NEx
pa_pre na_pre U2P_pre PEx_pre NEx_pre
pa_post na_post U2P_post PEx_post NEx_post
ham_pre ham_post group;
CLUSTER = ID;
USEVAR = na_pre ue_pre;
MISSING = ALL(-999);
DEFINE: ue_pre = -1*U2P_pre;
ANALYSIS: TYPE = TWOLEVEL;
ESTIMATOR = BAYES;
PROC = 2;
BITER = (3000);
BSEED = 6974;
THIN = 5;
MODEL:
%WITHIN%
na_pre WITH ue_pre;
na_pre (wvar_na);
ue_pre (wvar_ue);
%BETWEEN%
na_pre WITH ue_pre;
na_pre (bvar_na);
ue_pre (bvar_ue);
MODEL CONSTRAINT:
NEW (icc_na); icc_na = bvar_na/(bvar_na + wvar_na);
NEW (icc_ue); icc_ue = bvar_ue/(bvar_ue + wvar_ue);
OUTPUT: TECH1 TECH8 STDYX FSCOMPARISON;
PLOT: TYPE = PLOT3;
FACTOR =ALL;
*** WARNING
Data set contains cases with missing on all variables.
These cases were not included in the analysis.
Number of cases with missing on all variables: 5643
1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
Multilevel model for decomposition into
within and between variance
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 6170
Number of dependent variables 2
Number of independent variables 0
Number of continuous latent variables 0
Observed dependent variables
Continuous
NA_PRE UE_PRE
Variables with special functions
Cluster variable ID
Estimator BAYES
Specifications for Bayesian Estimation
Point estimate MEDIAN
Number of Markov chain Monte Carlo (MCMC) chains 2
Random seed for the first chain 6974
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 5
Specifications for Bayes Factor Score Estimation
Number of imputed data sets 50
Iteration intervals for thinning 1
Input data file(s)
ChapterData1.dat
Input data format FREE
SUMMARY OF DATA
Number of clusters 129
Size (s) Cluster ID with Size s
20 120
22 143
29 72
30 46 66
33 49
35 107 69
36 45 41 43 54 95 12
37 58 26 140
39 102 136 91 27
40 20 131 17 28
41 130
42 90 82 137 23
43 30
44 19 10 121 125 73 92 83 86
45 122 110 60
46 7 81 36 38 113 97 144 1
47 37 39 80 84 85
48 104 79 135 64 14
49 76 48 129 59
50 33 71 118 21 70 22 124 47
51 62 32 8 134 112 94 11 101 55
52 53 68 44 34 109 128 56
53 88 52 139
54 35 108 40 9 105 115 106 78 50 16
55 3 29 126 61 103 138
56 117 127 13 141 2 98 99
57 100 116 51 123 114 4
58 5 42 119 18
59 31 15 63
60 24 57
SUMMARY OF MISSING DATA PATTERNS
Number of missing data patterns 3
MISSING DATA PATTERNS (x = not missing)
1 2 3
NA_PRE x x
UE_PRE x x
MISSING DATA PATTERN FREQUENCIES
Pattern Frequency Pattern Frequency Pattern Frequency
1 5994 2 172 3 4
COVARIANCE COVERAGE OF DATA
Minimum covariance coverage value 0.100
PROPORTION OF DATA PRESENT
Covariance Coverage
NA_PRE UE_PRE
________ ________
NA_PRE 0.999
UE_PRE 0.971 0.972
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
NA_PRE 2.048 1.291 1.000 20.73% 1.000 1.430 1.710
6166.000 1.197 1.382 7.000 0.08% 2.000 2.860
UE_PRE -1.247 1.014 -3.000 28.36% -3.000 -2.000 -2.000
5998.000 3.104 0.082 3.000 5.94% -1.000 0.000
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 8
Bayesian Posterior Predictive Checking using Chi-Square
95% Confidence Interval for the Difference Between
the Observed and the Replicated Chi-Square Values
-12.243 12.604
Posterior Predictive P-Value 0.500
Information Criteria
Deviance (DIC) 38096.713
Estimated Number of Parameters (pD) 230.630
MODEL RESULTS
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Within Level
NA_PRE WITH
UE_PRE 0.415 0.019 0.000 0.378 0.452 *
Variances
NA_PRE 0.682 0.012 0.000 0.659 0.707 *
UE_PRE 2.842 0.052 0.000 2.742 2.945 *
Between Level
NA_PRE WITH
UE_PRE 0.171 0.045 0.000 0.090 0.266 *
Means
NA_PRE 2.068 0.067 0.000 1.936 2.200 *
UE_PRE -1.246 0.052 0.000 -1.346 -1.144 *
Variances
NA_PRE 0.569 0.077 0.000 0.443 0.742 *
UE_PRE 0.287 0.047 0.000 0.213 0.392 *
New/Additional Parameters
ICC_NA 0.455 0.033 0.000 0.392 0.523 *
ICC_UE 0.092 0.014 0.000 0.070 0.121 *
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
NA_PRE WITH
UE_PRE 0.298 0.012 0.000 0.275 0.321 *
Variances
NA_PRE 1.000 0.000 0.000 1.000 1.000
UE_PRE 1.000 0.000 0.000 1.000 1.000
Between Level
NA_PRE WITH
UE_PRE 0.426 0.084 0.000 0.245 0.572 *
Means
NA_PRE 2.740 0.202 0.000 2.359 3.153 *
UE_PRE -2.322 0.211 0.000 -2.769 -1.931 *
Variances
NA_PRE 1.000 0.000 0.000 1.000 1.000
UE_PRE 1.000 0.000 0.000 1.000 1.000
BETWEEN-LEVEL FACTOR SCORE COMPARISONS
Results for NA_PRE (referred to as plausible label B_NA_PRE)
Ranking Cluster Factor Score Ranking Cluster Factor Score Ranking Cluster Factor Score
1 134 4.111 2 120 4.068 3 124 3.931
4 28 3.681 5 27 3.600 6 49 3.537
7 13 3.484 8 66 3.484 9 39 3.436
10 107 3.360 11 68 3.335 12 117 3.334
13 121 3.316 14 40 3.307 15 64 3.296
16 138 3.276 17 76 3.181 18 17 3.106
19 82 3.062 20 127 2.938 21 69 2.884
22 70 2.745 23 81 2.739 24 131 2.734
25 122 2.715 26 139 2.690 27 104 2.621
28 105 2.589 29 137 2.567 30 103 2.556
31 8 2.487 32 50 2.447 33 72 2.424
34 100 2.406 35 95 2.342 36 16 2.330
37 31 2.306 38 140 2.262 39 116 2.244
40 22 2.238 41 1 2.228 42 9 2.213
43 135 2.209 44 106 2.202 45 79 2.198
46 58 2.197 47 94 2.190 48 18 2.165
49 32 2.136 50 23 2.129 51 71 2.113
52 57 2.084 53 30 2.083 54 97 2.080
55 10 2.065 56 78 2.061 57 15 2.048
58 123 2.029 59 5 2.001 60 19 1.996
61 125 1.978 62 136 1.965 63 55 1.917
64 36 1.910 65 46 1.897 66 119 1.886
67 21 1.883 68 59 1.854 69 4 1.839
70 130 1.829 71 126 1.767 72 29 1.765
73 128 1.763 74 20 1.759 75 114 1.748
76 7 1.748 77 90 1.739 78 53 1.731
79 143 1.722 80 61 1.718 81 54 1.698
82 52 1.686 83 37 1.684 84 3 1.665
85 62 1.638 86 129 1.630 87 48 1.619
88 41 1.615 89 26 1.568 90 102 1.561
91 24 1.549 92 88 1.536 93 108 1.536
94 56 1.525 95 11 1.514 96 51 1.510
97 85 1.495 98 60 1.479 99 33 1.476
100 92 1.462 101 73 1.429 102 44 1.421
103 2 1.409 104 109 1.408 105 83 1.397
106 118 1.364 107 98 1.361 108 115 1.351
109 14 1.350 110 38 1.347 111 45 1.341
112 47 1.338 113 112 1.333 114 42 1.328
115 141 1.313 116 110 1.299 117 80 1.287
118 144 1.268 119 113 1.260 120 101 1.260
121 86 1.252 122 35 1.237 123 91 1.215
124 34 1.207 125 63 1.202 126 84 1.189
127 12 1.143 128 99 1.079 129 43 1.035
Results for UE_PRE (referred to as plausible label B_UE_PRE)
Ranking Cluster Factor Score Ranking Cluster Factor Score Ranking Cluster Factor Score
1 49 -0.045 2 82 -0.141 3 81 -0.251
4 117 -0.348 5 59 -0.426 6 60 -0.483
7 32 -0.503 8 134 -0.517 9 41 -0.562
10 127 -0.571 11 105 -0.580 12 53 -0.596
13 18 -0.619 14 139 -0.626 15 69 -0.645
16 95 -0.682 17 109 -0.693 18 44 -0.720
19 5 -0.775 20 78 -0.808 21 120 -0.813
22 34 -0.816 23 17 -0.818 24 140 -0.821
25 13 -0.822 26 125 -0.840 27 45 -0.843
28 3 -0.860 29 114 -0.869 30 20 -0.873
31 11 -0.881 32 31 -0.892 33 27 -0.917
34 94 -0.925 35 121 -0.927 36 90 -0.947
37 137 -0.956 38 64 -0.962 39 62 -0.979
40 15 -1.000 41 22 -1.000 42 131 -1.015
43 30 -1.015 44 128 -1.038 45 72 -1.062
46 16 -1.065 47 100 -1.070 48 50 -1.100
49 70 -1.104 50 76 -1.104 51 138 -1.119
52 7 -1.131 53 68 -1.133 54 123 -1.135
55 119 -1.136 56 4 -1.137 57 115 -1.139
58 9 -1.143 59 124 -1.148 60 104 -1.154
61 48 -1.156 62 51 -1.214 63 58 -1.214
64 38 -1.245 65 1 -1.246 66 107 -1.247
67 8 -1.248 68 122 -1.261 69 71 -1.282
70 37 -1.312 71 86 -1.315 72 101 -1.316
73 21 -1.322 74 136 -1.329 75 56 -1.340
76 57 -1.344 77 36 -1.345 78 103 -1.347
79 106 -1.351 80 126 -1.378 81 63 -1.385
82 143 -1.406 83 40 -1.426 84 29 -1.438
85 116 -1.442 86 55 -1.452 87 66 -1.458
88 61 -1.464 89 73 -1.471 90 79 -1.473
91 80 -1.493 92 129 -1.496 93 112 -1.513
94 144 -1.537 95 28 -1.554 96 12 -1.565
97 141 -1.577 98 52 -1.591 99 10 -1.595
100 23 -1.605 101 110 -1.636 102 92 -1.657
103 47 -1.663 104 14 -1.667 105 24 -1.693
106 97 -1.698 107 43 -1.718 108 102 -1.720
109 113 -1.740 110 130 -1.780 111 39 -1.805
112 99 -1.866 113 26 -1.892 114 108 -1.893
115 2 -1.895 116 54 -1.919 117 46 -1.937
118 88 -1.937 119 85 -1.956 120 118 -1.978
121 83 -2.005 122 33 -2.017 123 135 -2.041
124 19 -2.043 125 98 -2.066 126 91 -2.088
127 84 -2.178 128 42 -2.199 129 35 -2.351
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR WITHIN
NU
NA_PRE UE_PRE
________ ________
0 0
THETA
NA_PRE UE_PRE
________ ________
NA_PRE 1
UE_PRE 2 3
PARAMETER SPECIFICATION FOR BETWEEN
NU
NA_PRE UE_PRE
________ ________
4 5
THETA
NA_PRE UE_PRE
________ ________
NA_PRE 6
UE_PRE 7 8
PARAMETER SPECIFICATION FOR THE ADDITIONAL PARAMETERS
NEW/ADDITIONAL PARAMETERS
ICC_NA ICC_UE
________ ________
9 10
STARTING VALUES FOR WITHIN
NU
NA_PRE UE_PRE
________ ________
0.000 0.000
THETA
NA_PRE UE_PRE
________ ________
NA_PRE 0.598
UE_PRE 0.000 1.552
STARTING VALUES FOR BETWEEN
NU
NA_PRE UE_PRE
________ ________
2.048 -1.247
THETA
NA_PRE UE_PRE
________ ________
NA_PRE 0.598
UE_PRE 0.000 1.552
STARTING VALUES FOR THE ADDITIONAL PARAMETERS
NEW/ADDITIONAL PARAMETERS
ICC_NA ICC_UE
________ ________
0.500 0.500
PRIORS FOR ALL PARAMETERS PRIOR MEAN PRIOR VARIANCE PRIOR STD. DEV.
Parameter 1~IW(0.000,-3) infinity infinity infinity
Parameter 2~IW(0.000,-3) infinity infinity infinity
Parameter 3~IW(0.000,-3) infinity infinity infinity
Parameter 4~N(0.000,infinity) 0.0000 infinity infinity
Parameter 5~N(0.000,infinity) 0.0000 infinity infinity
Parameter 6~IW(0.000,-3) infinity infinity infinity
Parameter 7~IW(0.000,-3) infinity infinity infinity
Parameter 8~IW(0.000,-3) infinity infinity infinity
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR BAYES ESTIMATION
CHAIN BSEED
1 6974
2 534401
POTENTIAL PARAMETER WITH
ITERATION SCALE REDUCTION HIGHEST PSR
100 1.000 1
200 1.015 2
300 1.015 2
400 1.020 8
500 1.012 8
600 1.006 8
700 1.003 6
800 1.002 6
900 1.003 6
1000 1.004 6
1100 1.002 6
1200 1.001 6
1300 1.003 6
1400 1.002 6
1500 1.003 6
1600 1.004 6
1700 1.002 6
1800 1.001 6
1900 1.002 6
2000 1.001 6
2100 1.001 6
2200 1.000 6
2300 1.001 5
2400 1.001 5
2500 1.001 5
2600 1.000 5
2700 1.000 5
2800 1.000 2
2900 1.000 5
3000 1.000 5
SUMMARIES OF PLAUSIBLE VALUES (N = NUMBER OF OBSERVATIONS * NUMBER OF IMPUTATIONS)
SAMPLE STATISTICS
Means
B_NA_PRE B_UE_PRE
________ ________
2.048 -1.249
Covariances
B_NA_PRE B_UE_PRE
________ ________
B_NA_PRE 0.517
B_UE_PRE 0.158 0.267
Correlations
B_NA_PRE B_UE_PRE
________ ________
B_NA_PRE 1.000
B_UE_PRE 0.426 1.000
SUMMARY OF PLAUSIBLE STANDARD DEVIATION (N = NUMBER OF OBSERVATIONS)
SAMPLE STATISTICS
Means
B_NA_PRE B_UE_PRE
________ ________
0.117 0.218
Covariances
B_NA_PRE B_UE_PRE
________ ________
B_NA_PRE 0.000
B_UE_PRE 0.000 0.001
Correlations
B_NA_PRE B_UE_PRE
________ ________
B_NA_PRE 1.000
B_UE_PRE 0.394 1.000
PLOT INFORMATION
The following plots are available:
Histograms (sample values, estimated factor scores)
Scatterplots (sample values, estimated factor scores)
Between-level histograms (sample values, sample means/variances, estimated factor scores)
Between-level scatterplots (sample values, sample means/variances, estimated factor scores)
Bayesian posterior parameter distributions
Bayesian posterior parameter trace plots
Bayesian autocorrelation plots
Bayesian posterior predictive checking scatterplots
Bayesian posterior predictive checking distribution plots
Latent variable distribution plots
DIAGRAM INFORMATION
Mplus diagrams are currently not available for multilevel analysis.
No diagram output was produced.
Beginning Time: 09:38:24
Ending Time: 09:38:42
Elapsed Time: 00:00:18
MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA 90066
Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com
Copyright (c) 1998-2021 Muthen & Muthen