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<!DOCTYPE html>
<style>
ul {
list-style-type: none;
margin: 0;
padding: 0;
}
a:link
{
color: black;
text-decoration: none;
}
a[name]:hover
{
text-decoration: none;
}
a:hover
{
color: blue;
text-decoration: underline;
}
a:visited
{
color: black;
text-decoration: none;
}
.heading
{
color: black;
font-weight: bold;
font-size: 110%;
}
.heading:hover
{
color: black;
font-weight: bold;
font-size: 110%;
text-decoration: none;
}
</style>
<body style="font-family:'Courier New'; font-size:14px;">
<p class="heading">
Mplus VERSION 8.6<br />
MUTHEN & MUTHEN<br />
05/18/2021 10:45 AM<br />
</p>
<p class='heading'>OUTPUT SECTIONS</p>
<ul>
<li><a href='#input'>Input Instructions</a></li>
<li><a href='#inputmessages'>Input Warnings And Errors</a></li>
<li><a href='#summary_analysis'>Summary Of Analysis</a></li>
<li><a href='#summary_data'>Summary Of Data</a></li>
<li><a href='#summary_missing_patterns'>Summary Of Missing Data Patterns</a></li>
<li><a href='#covariance_coverage'>Covariance Coverage Of Data</a></li>
<li><a href='#univariatess'>Univariate Sample Statistics</a></li>
<li><a href='#modelmessages'>Model Warnings And Errors</a></li>
<li><a href='#model_fit'>Model Fit Information</a></li>
<li><a href='#model_results'>Model Results</a></li>
<li><a href='#standardized_results'>Standardized Model Results</a></li>
<li><a href='#rsquare'>R-square</a></li>
<li>Within-level Standardized Model Results For Each Cluster</li>
<a href='#standardized_within_120'>120</a>
<a href='#standardized_within_122'>122</a>
<a href='#standardized_within_136'>136</a>
<a href='#standardized_within_23'>23</a>
<a href='#standardized_within_66'>66</a>
<a href='#standardized_within_37'>37</a>
<a href='#standardized_within_39'>39</a>
<a href='#standardized_within_72'>72</a>
<a href='#standardized_within_69'>69</a>
<a href='#standardized_within_26'>26</a>
<a href='#standardized_within_58'>58</a>
<a href='#standardized_within_130'>130</a>
<a href='#standardized_within_64'>64</a>
<a href='#standardized_within_115'>115</a>
<a href='#standardized_within_38'>38</a>
<a href='#standardized_within_125'>125</a>
<a href='#standardized_within_107'>107</a>
<a href='#standardized_within_62'>62</a>
<a href='#standardized_within_124'>124</a>
<a href='#standardized_within_17'>17</a>
<a href='#standardized_within_110'>110</a>
<a href='#standardized_within_27'>27</a>
<a href='#standardized_within_86'>86</a>
<a href='#standardized_within_56'>56</a>
<a href='#standardized_within_70'>70</a>
<a href='#standardized_within_30'>30</a>
<a href='#standardized_within_134'>134</a>
<a href='#standardized_within_139'>139</a>
<a href='#standardized_within_140'>140</a>
<a href='#standardized_within_44'>44</a>
<a href='#standardized_within_46'>46</a>
<a href='#standardized_within_126'>126</a>
<a href='#standardized_within_143'>143</a>
<a href='#standardized_within_102'>102</a>
<a href='#standardized_within_7'>7</a>
<a href='#standardized_within_129'>129</a>
<a href='#standardized_within_19'>19</a>
<a href='#standardized_within_9'>9</a>
<a href='#standardized_within_82'>82</a>
<a href='#standardized_within_8'>8</a>
<a href='#standardized_within_52'>52</a>
<a href='#standardized_within_54'>54</a>
<a href='#standardized_within_105'>105</a>
<a href='#standardized_within_85'>85</a>
<a href='#standardized_within_57'>57</a>
<a href='#standardized_within_116'>116</a>
<a href='#standardized_within_32'>32</a>
<a href='#standardized_within_63'>63</a>
<a href='#standardized_within_36'>36</a>
<a href='#standardized_within_10'>10</a>
<a href='#standardized_within_95'>95</a>
<a href='#standardized_within_71'>71</a>
<a href='#standardized_within_21'>21</a>
<a href='#standardized_within_79'>79</a>
<a href='#standardized_within_40'>40</a>
<a href='#standardized_within_88'>88</a>
<a href='#standardized_within_80'>80</a>
<a href='#standardized_within_41'>41</a>
<a href='#standardized_within_81'>81</a>
<a href='#standardized_within_12'>12</a>
<a href='#standardized_within_144'>144</a>
<a href='#standardized_within_108'>108</a>
<a href='#standardized_within_73'>73</a>
<a href='#standardized_within_49'>49</a>
<a href='#standardized_within_43'>43</a>
<a href='#standardized_within_1'>1</a>
<a href='#standardized_within_90'>90</a>
<a href='#standardized_within_121'>121</a>
<a href='#standardized_within_123'>123</a>
<a href='#standardized_within_28'>28</a>
<a href='#standardized_within_13'>13</a>
<a href='#standardized_within_119'>119</a>
<a href='#standardized_within_4'>4</a>
<a href='#standardized_within_91'>91</a>
<a href='#standardized_within_16'>16</a>
<a href='#standardized_within_47'>47</a>
<a href='#standardized_within_83'>83</a>
<a href='#standardized_within_5'>5</a>
<a href='#standardized_within_117'>117</a>
<a href='#standardized_within_138'>138</a>
<a href='#standardized_within_45'>45</a>
<a href='#standardized_within_42'>42</a>
<a href='#standardized_within_24'>24</a>
<a href='#standardized_within_103'>103</a>
<a href='#standardized_within_50'>50</a>
<a href='#standardized_within_2'>2</a>
<a href='#standardized_within_106'>106</a>
<a href='#standardized_within_18'>18</a>
<a href='#standardized_within_109'>109</a>
<a href='#standardized_within_53'>53</a>
<a href='#standardized_within_112'>112</a>
<a href='#standardized_within_113'>113</a>
<a href='#standardized_within_76'>76</a>
<a href='#standardized_within_29'>29</a>
<a href='#standardized_within_118'>118</a>
<a href='#standardized_within_55'>55</a>
<a href='#standardized_within_3'>3</a>
<a href='#standardized_within_14'>14</a>
<a href='#standardized_within_22'>22</a>
<a href='#standardized_within_84'>84</a>
<a href='#standardized_within_61'>61</a>
<a href='#standardized_within_127'>127</a>
<a href='#standardized_within_15'>15</a>
<a href='#standardized_within_34'>34</a>
<a href='#standardized_within_92'>92</a>
<a href='#standardized_within_131'>131</a>
<a href='#standardized_within_35'>35</a>
<a href='#standardized_within_11'>11</a>
<a href='#standardized_within_97'>97</a>
<a href='#standardized_within_68'>68</a>
<a href='#standardized_within_99'>99</a>
<a href='#standardized_within_100'>100</a>
<a href='#standardized_within_141'>141</a>
<a href='#standardized_within_101'>101</a>
<a href='#standardized_within_48'>48</a>
<a href='#standardized_within_51'>51</a>
<a href='#standardized_within_135'>135</a>
<a href='#standardized_within_137'>137</a>
<a href='#standardized_within_114'>114</a>
<a href='#standardized_within_128'>128</a>
<a href='#standardized_within_20'>20</a>
<a href='#standardized_within_98'>98</a>
<a href='#standardized_within_104'>104</a>
<a href='#standardized_within_78'>78</a>
<a href='#standardized_within_31'>31</a>
<a href='#standardized_within_94'>94</a>
<a href='#standardized_within_59'>59</a>
<a href='#standardized_within_60'>60</a>
<a href='#standardized_within_33'>33</a>
<li>Within-level R-square For Each Cluster</li>
<a href='#rsquare_within_120'>120</a>
<a href='#rsquare_within_122'>122</a>
<a href='#rsquare_within_136'>136</a>
<a href='#rsquare_within_23'>23</a>
<a href='#rsquare_within_66'>66</a>
<a href='#rsquare_within_37'>37</a>
<a href='#rsquare_within_39'>39</a>
<a href='#rsquare_within_72'>72</a>
<a href='#rsquare_within_69'>69</a>
<a href='#rsquare_within_26'>26</a>
<a href='#rsquare_within_58'>58</a>
<a href='#rsquare_within_130'>130</a>
<a href='#rsquare_within_64'>64</a>
<a href='#rsquare_within_115'>115</a>
<a href='#rsquare_within_38'>38</a>
<a href='#rsquare_within_125'>125</a>
<a href='#rsquare_within_107'>107</a>
<a href='#rsquare_within_62'>62</a>
<a href='#rsquare_within_124'>124</a>
<a href='#rsquare_within_17'>17</a>
<a href='#rsquare_within_110'>110</a>
<a href='#rsquare_within_27'>27</a>
<a href='#rsquare_within_86'>86</a>
<a href='#rsquare_within_56'>56</a>
<a href='#rsquare_within_70'>70</a>
<a href='#rsquare_within_30'>30</a>
<a href='#rsquare_within_134'>134</a>
<a href='#rsquare_within_139'>139</a>
<a href='#rsquare_within_140'>140</a>
<a href='#rsquare_within_44'>44</a>
<a href='#rsquare_within_46'>46</a>
<a href='#rsquare_within_126'>126</a>
<a href='#rsquare_within_143'>143</a>
<a href='#rsquare_within_102'>102</a>
<a href='#rsquare_within_7'>7</a>
<a href='#rsquare_within_129'>129</a>
<a href='#rsquare_within_19'>19</a>
<a href='#rsquare_within_9'>9</a>
<a href='#rsquare_within_82'>82</a>
<a href='#rsquare_within_8'>8</a>
<a href='#rsquare_within_52'>52</a>
<a href='#rsquare_within_54'>54</a>
<a href='#rsquare_within_105'>105</a>
<a href='#rsquare_within_85'>85</a>
<a href='#rsquare_within_57'>57</a>
<a href='#rsquare_within_116'>116</a>
<a href='#rsquare_within_32'>32</a>
<a href='#rsquare_within_63'>63</a>
<a href='#rsquare_within_36'>36</a>
<a href='#rsquare_within_10'>10</a>
<a href='#rsquare_within_95'>95</a>
<a href='#rsquare_within_71'>71</a>
<a href='#rsquare_within_21'>21</a>
<a href='#rsquare_within_79'>79</a>
<a href='#rsquare_within_40'>40</a>
<a href='#rsquare_within_88'>88</a>
<a href='#rsquare_within_80'>80</a>
<a href='#rsquare_within_41'>41</a>
<a href='#rsquare_within_81'>81</a>
<a href='#rsquare_within_12'>12</a>
<a href='#rsquare_within_144'>144</a>
<a href='#rsquare_within_108'>108</a>
<a href='#rsquare_within_73'>73</a>
<a href='#rsquare_within_49'>49</a>
<a href='#rsquare_within_43'>43</a>
<a href='#rsquare_within_1'>1</a>
<a href='#rsquare_within_90'>90</a>
<a href='#rsquare_within_121'>121</a>
<a href='#rsquare_within_123'>123</a>
<a href='#rsquare_within_28'>28</a>
<a href='#rsquare_within_13'>13</a>
<a href='#rsquare_within_119'>119</a>
<a href='#rsquare_within_4'>4</a>
<a href='#rsquare_within_91'>91</a>
<a href='#rsquare_within_16'>16</a>
<a href='#rsquare_within_47'>47</a>
<a href='#rsquare_within_83'>83</a>
<a href='#rsquare_within_5'>5</a>
<a href='#rsquare_within_117'>117</a>
<a href='#rsquare_within_138'>138</a>
<a href='#rsquare_within_45'>45</a>
<a href='#rsquare_within_42'>42</a>
<a href='#rsquare_within_24'>24</a>
<a href='#rsquare_within_103'>103</a>
<a href='#rsquare_within_50'>50</a>
<a href='#rsquare_within_2'>2</a>
<a href='#rsquare_within_106'>106</a>
<a href='#rsquare_within_18'>18</a>
<a href='#rsquare_within_109'>109</a>
<a href='#rsquare_within_53'>53</a>
<a href='#rsquare_within_112'>112</a>
<a href='#rsquare_within_113'>113</a>
<a href='#rsquare_within_76'>76</a>
<a href='#rsquare_within_29'>29</a>
<a href='#rsquare_within_118'>118</a>
<a href='#rsquare_within_55'>55</a>
<a href='#rsquare_within_3'>3</a>
<a href='#rsquare_within_14'>14</a>
<a href='#rsquare_within_22'>22</a>
<a href='#rsquare_within_84'>84</a>
<a href='#rsquare_within_61'>61</a>
<a href='#rsquare_within_127'>127</a>
<a href='#rsquare_within_15'>15</a>
<a href='#rsquare_within_34'>34</a>
<a href='#rsquare_within_92'>92</a>
<a href='#rsquare_within_131'>131</a>
<a href='#rsquare_within_35'>35</a>
<a href='#rsquare_within_11'>11</a>
<a href='#rsquare_within_97'>97</a>
<a href='#rsquare_within_68'>68</a>
<a href='#rsquare_within_99'>99</a>
<a href='#rsquare_within_100'>100</a>
<a href='#rsquare_within_141'>141</a>
<a href='#rsquare_within_101'>101</a>
<a href='#rsquare_within_48'>48</a>
<a href='#rsquare_within_51'>51</a>
<a href='#rsquare_within_135'>135</a>
<a href='#rsquare_within_137'>137</a>
<a href='#rsquare_within_114'>114</a>
<a href='#rsquare_within_128'>128</a>
<a href='#rsquare_within_20'>20</a>
<a href='#rsquare_within_98'>98</a>
<a href='#rsquare_within_104'>104</a>
<a href='#rsquare_within_78'>78</a>
<a href='#rsquare_within_31'>31</a>
<a href='#rsquare_within_94'>94</a>
<a href='#rsquare_within_59'>59</a>
<a href='#rsquare_within_60'>60</a>
<a href='#rsquare_within_33'>33</a>
<li><a href='#bayes_fscores_comparisons'>Between-level Factor Score Comparisons</a></li>
<li><a href='#tech1_output'>Technical 1 Output</a></li>
<li><a href='#tech8_output'>Technical 8 Output</a></li>
<li><a href='#summary_plausible'>Summaries Of Plausible Values (n = Number Of Observations * Number Of Imputations)</a></li>
<li><a href='#summary_plausible_stdev'>Summary Of Plausible Standard Deviation (n = Number Of Observations)</a></li>
<li><a href='#plot_info'>Plot Information</a></li>
</ul>
<pre>
<a name='input' class='heading'>INPUT INSTRUCTIONS</a>
TITLE: Multilevel VAR(1) for negative affect (NA) and
unpleasant experiences (UE; recoded).
With level:
- random means for both variables
- random slopes
- random varianes
Between level:
- correlated random effects
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;
LAGGED = na_pre(1) ue_pre(1);
TINTERVAL = TimeHours(1);
MISSING = ALL(-999);
DEFINE: ue_pre = -1*U2P_pre;
ANALYSIS: TYPE = TWOLEVEL RANDOM;
ESTIMATOR = BAYES;
PROC = 2;
BITER = (3000);
BSEED = 6643;
THIN = 5;
MODEL:
%WITHIN%
phi_na | na_pre ON na_pre&1; ! autoregression NA (lag 1)
beta_na | na_pre ON ue_pre; ! cross-regression from UE to NA (lag 0)
phi_ue | ue_pre ON ue_pre&1; ! autoregression UE (lag 1)
beta_ue | ue_pre on na_pre&1; ! cross-lagged regression from NA to UE (lag 1)
psi_na | na_pre; ! random residual variance NA
psi_ue | ue_pre; ! random residual variance UE
%BETWEEN%
! allow all random effects to be correlated
na_pre ue_pre phi_na-psi_ue WITH ue_pre phi_na-psi_ue;
OUTPUT: TECH1 TECH8 STDYX FSCOMPARISON STAND(CLUSTER);
PLOT: TYPE = PLOT3;
FACTOR = ALL (500);
<a name='inputmessages' class='heading'></a>
*** WARNING
Data set contains cases with missing on all variables. Cases that appeared before the first
case with observed data and that appeared after the last case with observed data were not
included in the analysis. Number of deleted cases: 37218
1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
Multilevel VAR(1) for negative affect (NA) and
unpleasant experiences (UE; recoded).
With level:
- random means for both variables
- random slopes
- random varianes
Between level:
- correlated random effects
<a name='summary_analysis' class='heading'>SUMMARY OF ANALYSIS</a>
Number of groups 1
Number of observations 17349
Number of dependent variables 2
Number of independent variables 2
Number of continuous latent variables 6
Observed dependent variables
Continuous
NA_PRE UE_PRE
Observed independent variables
NA_PRE&1 UE_PRE&1
Continuous latent variables
PHI_NA BETA_NA PHI_UE BETA_UE PSI_NA PSI_UE
Variables with special functions
Cluster variable ID
Within variables
NA_PRE&1 UE_PRE&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 6643
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 500
Iteration intervals for thinning 1
Input data file(s)
ChapterData1.dat
Input data format FREE
<a name='summary_data' class='heading'>SUMMARY OF DATA</a>
Number of clusters 129
Size (s) Cluster ID with Size s
48 120
103 122
123 136
124 23
126 66
127 37 39
128 72
129 69 26 58 130 64 115
130 38 125 107 62 124 17 110
131 27 86 56 70 30 134 139 140 44 46
132 126 143 102 7 129 19 9 82
133 8 52 54 105 85 57 116 32 63 36 10 95 71 21 79 40 88
80 41 81 12 144 108 73 49 43 1 90
134 121 123 28 13 119 4 91 16 47 83 5 117 138 45 42 24 103
50 2 106 18 109 53 112 113 76 29 118 55 3 14 22 84 61
127 15 34 92 131 35 11 97 68 99 100 141 101 48 51 135
137 114 128 20 98
152 104
158 78
175 31
177 94
182 59
201 60
254 33
<a name='summary_missing_patterns' class='heading'>SUMMARY OF MISSING DATA PATTERNS</a>
Number of missing data patterns 12
MISSING DATA PATTERNS (x = not missing)
1 2 3 4 5 6 7 8 9 10 11 12
NA_PRE x x x x x x x
UE_PRE x x x x x
NA_PRE&1 x x x x x x
UE_PRE&1 x x x x x
MISSING DATA PATTERN FREQUENCIES
Pattern Frequency Pattern Frequency Pattern Frequency
1 2547 5 60 9 13
2 3386 6 96 10 4
3 3262 7 99 11 2
4 7819 8 59 12 2
<a name='covariance_coverage' class='heading'>COVARIANCE COVERAGE OF DATA</a>
Minimum covariance coverage value 0.100
PROPORTION OF DATA PRESENT
Covariance Coverage
NA_PRE UE_PRE
________ ________
NA_PRE 0.355
UE_PRE 0.345 0.346
<a name='univariatess' class='heading'>UNIVARIATE SAMPLE STATISTICS</a>
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
<a name='modelmessages' class='heading'></a>
WARNING: PROBLEMS OCCURRED IN SEVERAL ITERATIONS IN THE COMPUTATION OF THE STANDARDIZED ESTIMATES FOR SEVERAL
CLUSTERS. THIS IS MOST LIKELY DUE TO AR COEFFICIENTS GREATER THAN 1 OR PARAMETERS GIVING NON-STATIONARY MODELS.
SUCH POSTERIOR DRAWS ARE REMOVED. THE FOLLOWING CLUSTERS HAD SUCH PROBLEMS:
120 66 39 134 116 144 28 117 3 141
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.
<a name='model_fit' class='heading'>MODEL FIT INFORMATION</a>
Number of Free Parameters 44
Information Criteria
Deviance (DIC) 115150.507
Estimated Number of Parameters (pD) 22018.773
<a name='model_results' class='heading'>MODEL RESULTS</a>
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Within Level
Between Level
NA_PRE WITH
PHI_NA 0.029 0.020 0.072 -0.012 0.068
BETA_NA 0.030 0.008 0.000 0.017 0.047 *
PHI_UE 0.007 0.024 0.374 -0.039 0.055
BETA_UE -0.062 0.038 0.036 -0.145 0.005
PSI_NA 0.505 0.091 0.000 0.352 0.705 *
PSI_UE -0.001 0.045 0.491 -0.087 0.087
UE_PRE WITH
PHI_NA 0.011 0.016 0.246 -0.020 0.044
BETA_NA 0.007 0.005 0.069 -0.002 0.018
PHI_UE 0.013 0.018 0.238 -0.024 0.047
BETA_UE -0.005 0.030 0.436 -0.069 0.051
PSI_NA 0.179 0.065 0.002 0.063 0.318 *
PSI_UE 0.104 0.037 0.001 0.036 0.182 *
PHI_NA WITH
BETA_NA -0.002 0.002 0.146 -0.007 0.002
PHI_UE -0.003 0.007 0.335 -0.018 0.011
BETA_UE 0.006 0.013 0.303 -0.021 0.030
PSI_NA 0.023 0.028 0.195 -0.030 0.080
PSI_UE 0.001 0.015 0.472 -0.028 0.032
BETA_NA WITH
PHI_UE 0.003 0.002 0.091 -0.002 0.008
BETA_UE -0.007 0.004 0.017 -0.016 -0.001 *
PSI_NA 0.040 0.009 0.000 0.024 0.061 *
PSI_UE -0.006 0.005 0.136 -0.016 0.005
PHI_UE WITH
BETA_UE -0.008 0.013 0.244 -0.036 0.016
PSI_NA 0.026 0.029 0.189 -0.031 0.082
PSI_UE 0.012 0.015 0.202 -0.017 0.042
BETA_UE WITH
PSI_NA -0.147 0.062 0.003 -0.294 -0.043 *
PSI_UE 0.025 0.022 0.106 -0.016 0.072
PSI_NA WITH
PSI_UE 0.068 0.058 0.112 -0.043 0.187
NA_PRE WITH
UE_PRE 0.178 0.050 0.000 0.090 0.287 *
Means
NA_PRE 2.035 0.068 0.000 1.903 2.172 *
UE_PRE -1.261 0.056 0.000 -1.369 -1.154 *
PHI_NA 0.470 0.024 0.000 0.421 0.516 *
BETA_NA 0.111 0.008 0.000 0.095 0.127 *
PHI_UE 0.128 0.026 0.000 0.076 0.177 *
BETA_UE 0.255 0.051 0.000 0.164 0.362 *
PSI_NA -1.160 0.088 0.000 -1.329 -0.982 *
PSI_UE 0.873 0.052 0.000 0.767 0.977 *
Variances
NA_PRE 0.556 0.084 0.000 0.421 0.744 *
UE_PRE 0.321 0.054 0.000 0.232 0.440 *
PHI_NA 0.051 0.010 0.000 0.035 0.074 *
BETA_NA 0.004 0.001 0.000 0.002 0.006 *
PHI_UE 0.032 0.010 0.000 0.015 0.055 *
BETA_UE 0.070 0.032 0.000 0.029 0.149 *
PSI_NA 0.976 0.146 0.000 0.733 1.311 *
PSI_UE 0.292 0.047 0.000 0.215 0.396 *
<a name='standardized_results' class='heading'>STANDARDIZED MODEL RESULTS</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Within-Level Standardized Estimates Averaged Over Clusters
PHI_NA | NA_PRE ON
NA_PRE&1 0.470 0.013 0.000 0.443 0.495 *
BETA_NA | NA_PRE ON
UE_PRE 0.232 0.011 0.000 0.210 0.252 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.129 0.020 0.000 0.089 0.166 *
BETA_UE | UE_PRE ON
NA_PRE&1 0.102 0.017 0.000 0.071 0.137 *
PSI_NA |
NA_PRE 0.637 0.012 0.000 0.613 0.659 *
PSI_UE |
UE_PRE 0.922 0.010 0.000 0.902 0.941 *
Between Level
NA_PRE WITH
PHI_NA 0.172 0.114 0.072 -0.071 0.390
BETA_NA 0.647 0.104 0.000 0.415 0.814 *
PHI_UE 0.055 0.172 0.374 -0.280 0.386
BETA_UE -0.329 0.166 0.036 -0.616 0.028
PSI_NA 0.692 0.056 0.000 0.568 0.786 *
PSI_UE -0.002 0.108 0.491 -0.210 0.208
UE_PRE WITH
PHI_NA 0.085 0.122 0.246 -0.154 0.321
BETA_NA 0.210 0.135 0.069 -0.066 0.456
PHI_UE 0.125 0.176 0.238 -0.243 0.457
BETA_UE -0.032 0.191 0.436 -0.408 0.347
PSI_NA 0.324 0.099 0.002 0.115 0.504 *
PSI_UE 0.346 0.103 0.001 0.130 0.525 *
PHI_NA WITH
BETA_NA -0.158 0.142 0.146 -0.410 0.146
PHI_UE -0.080 0.176 0.335 -0.410 0.274
BETA_UE 0.111 0.212 0.303 -0.304 0.524
PSI_NA 0.106 0.120 0.195 -0.136 0.331
PSI_UE 0.009 0.120 0.472 -0.225 0.247
BETA_NA WITH
PHI_UE 0.278 0.196 0.091 -0.138 0.631
BETA_UE -0.440 0.188 0.017 -0.765 -0.042 *
PSI_NA 0.645 0.086 0.000 0.448 0.789 *
PSI_UE -0.172 0.147 0.136 -0.434 0.135
PHI_UE WITH
BETA_UE -0.175 0.248 0.244 -0.574 0.408
PSI_NA 0.146 0.160 0.189 -0.178 0.443
PSI_UE 0.130 0.155 0.202 -0.178 0.433
BETA_UE WITH
PSI_NA -0.582 0.163 0.003 -0.825 -0.192 *
PSI_UE 0.185 0.147 0.106 -0.107 0.472
PSI_NA WITH
PSI_UE 0.130 0.104 0.112 -0.082 0.328
NA_PRE WITH
UE_PRE 0.428 0.090 0.000 0.230 0.586 *
Means
NA_PRE 2.732 0.212 0.000 2.327 3.160 *
UE_PRE -2.233 0.212 0.000 -2.686 -1.841 *
PHI_NA 2.092 0.247 0.000 1.649 2.625 *
BETA_NA 1.750 0.229 0.000 1.357 2.266 *
PHI_UE 0.722 0.191 0.000 0.386 1.143 *
BETA_UE 0.973 0.234 0.000 0.589 1.487 *
PSI_NA -1.171 0.124 0.000 -1.415 -0.935 *
PSI_UE 1.616 0.160 0.000 1.325 1.944 *
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
PHI_NA 1.000 0.000 0.000 1.000 1.000
BETA_NA 1.000 0.000 0.000 1.000 1.000
PHI_UE 1.000 0.000 0.000 1.000 1.000
BETA_UE 1.000 0.000 0.000 1.000 1.000
PSI_NA 1.000 0.000 0.000 1.000 1.000
PSI_UE 1.000 0.000 0.000 1.000 1.000
<a name='rsquare' class='heading'>R-SQUARE</a>
Within-Level R-Square Averaged Across Clusters
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.363 0.012 0.000 0.341 0.386
UE_PRE 0.078 0.010 0.000 0.059 0.098
<a name='standardized_within_120' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 120</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.498 0.170 0.005 0.135 0.804 *
BETA_NA | NA_PRE ON
UE_PRE 0.231 0.071 0.000 0.102 0.386 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.163 0.168 0.165 -0.195 0.482
BETA_UE | UE_PRE ON
NA_PRE&1 0.027 0.171 0.441 -0.328 0.358
PSI_NA |
NA_PRE 0.673 0.162 0.000 0.286 0.908 *
PSI_UE |
UE_PRE 0.937 0.082 0.000 0.704 0.997 *
<a name='rsquare_within_120' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 120</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.327 0.162 0.000 0.092 0.713
UE_PRE 0.063 0.082 0.000 0.003 0.294
<a name='standardized_within_122' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 122</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.445 0.139 0.002 0.153 0.696 *
BETA_NA | NA_PRE ON
UE_PRE 0.236 0.060 0.000 0.133 0.367 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.031 0.170 0.430 -0.322 0.334
BETA_UE | UE_PRE ON
NA_PRE&1 -0.084 0.136 0.251 -0.384 0.148
PSI_NA |
NA_PRE 0.757 0.116 0.000 0.485 0.929 *
PSI_UE |
UE_PRE 0.963 0.056 0.000 0.789 0.998 *
<a name='rsquare_within_122' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 122</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.243 0.116 0.000 0.070 0.513
UE_PRE 0.037 0.056 0.000 0.002 0.211
<a name='standardized_within_136' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 136</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.303 0.166 0.054 -0.090 0.562
BETA_NA | NA_PRE ON
UE_PRE 0.300 0.082 0.000 0.147 0.466 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.123 0.119 0.160 -0.121 0.351
BETA_UE | UE_PRE ON
NA_PRE&1 0.092 0.077 0.101 -0.062 0.250
PSI_NA |
NA_PRE 0.778 0.095 0.000 0.556 0.920 *
PSI_UE |
UE_PRE 0.962 0.046 0.000 0.830 0.998 *
<a name='rsquare_within_136' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 136</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.222 0.095 0.000 0.079 0.444
UE_PRE 0.038 0.046 0.000 0.002 0.170
<a name='standardized_within_23' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 23</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.337 0.144 0.019 0.032 0.595 *
BETA_NA | NA_PRE ON
UE_PRE 0.254 0.067 0.000 0.134 0.395 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.283 0.149 0.038 -0.028 0.565
BETA_UE | UE_PRE ON
NA_PRE&1 -0.027 0.127 0.417 -0.291 0.206
PSI_NA |
NA_PRE 0.804 0.097 0.000 0.563 0.940 *
PSI_UE |
UE_PRE 0.904 0.085 0.000 0.677 0.996 *
<a name='rsquare_within_23' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 23</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.196 0.097 0.000 0.060 0.436
UE_PRE 0.096 0.085 0.000 0.004 0.322
<a name='standardized_within_66' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 66</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.770 0.117 0.000 0.474 0.929 *
BETA_NA | NA_PRE ON
UE_PRE 0.167 0.074 0.002 0.036 0.328 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.134 0.160 0.207 -0.195 0.436
BETA_UE | UE_PRE ON
NA_PRE&1 0.307 0.149 0.008 0.050 0.637 *
PSI_NA |
NA_PRE 0.272 0.141 0.000 0.063 0.617 *
PSI_UE |
UE_PRE 0.828 0.131 0.000 0.457 0.974 *
<a name='rsquare_within_66' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 66</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.728 0.141 0.000 0.382 0.937
UE_PRE 0.172 0.131 0.000 0.025 0.543
<a name='standardized_within_37' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 37</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.224 0.130 0.045 -0.033 0.479
BETA_NA | NA_PRE ON
UE_PRE 0.323 0.077 0.000 0.169 0.473 *
PHI_UE | UE_PRE ON
UE_PRE&1 0.294 0.147 0.021 0.008 0.575 *
BETA_UE | UE_PRE ON
NA_PRE&1 0.010 0.096 0.449 -0.220 0.161
PSI_NA |
NA_PRE 0.814 0.082 0.000 0.616 0.938 *
PSI_UE |
UE_PRE 0.901 0.085 0.000 0.678 0.994 *
<a name='rsquare_within_37' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 37</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.186 0.082 0.000 0.062 0.384
UE_PRE 0.099 0.085 0.000 0.006 0.322
<a name='standardized_within_39' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 39</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.860 0.064 0.000 0.722 0.964 *
BETA_NA | NA_PRE ON
UE_PRE 0.090 0.037 0.001 0.029 0.168 *
PHI_UE | UE_PRE ON
UE_PRE&1 -0.003 0.158 0.495 -0.311 0.298
BETA_UE | UE_PRE ON
NA_PRE&1 0.186 0.168 0.113 -0.110 0.563
PSI_NA |
NA_PRE 0.220 0.104 0.000 0.043 0.444 *
PSI_UE |
UE_PRE 0.938 0.088 0.000 0.685 0.997 *
<a name='rsquare_within_39' class='heading'>WITHIN-LEVEL R-SQUARE FOR CLUSTER 39</a>
Posterior One-Tailed 95% C.I.
Variable Estimate S.D. P-Value Lower 2.5% Upper 2.5%
NA_PRE 0.780 0.104 0.000 0.554 0.956
UE_PRE 0.062 0.088 0.000 0.003 0.315
<a name='standardized_within_72' class='heading'>WITHIN-LEVEL STANDARDIZED MODEL RESULTS FOR CLUSTER 72</a>
STDYX Standardization
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
PHI_NA | NA_PRE ON
NA_PRE&1 0.569 0.127 0.000 0.282 0.793 *
BETA_NA | NA_PRE ON
UE_PRE 0.225 0.071 0.001 0.090 0.374 *
PHI_UE | UE_PRE ON