This chapter uses data set https://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt.
Table 8.1, page 282
Basic statistics and covariance matrix
TITLE:
alcohol2.inp DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 female peer1 peer2 peer3;
ANALYSIS:
Type = basic;
RESULTS FOR BASIC ANALYSIS
SAMPLE STATISTICS
Means
ALC1 ALC2 ALC3 FEMALE PEER1
________ ________ ________ ________ ________
1 0.225 0.254 0.288 0.612 0.177
Means
PEER2 PEER3
________ ________
1 0.290 0.347
Covariances
ALC1 ALC2 ALC3 FEMALE PEER1
________ ________ ________ ________ ________
ALC1 0.136
ALC2 0.078 0.155
ALC3 0.065 0.082 0.181
FEMALE -0.008 -0.013 -0.005 0.238
PEER1 0.066 0.045 0.040 -0.009 0.174
PEER2 0.064 0.096 0.066 -0.022 0.072
PEER3 0.060 0.074 0.132 -0.024 0.071
Covariances
PEER2 PEER3
________ ________
PEER2 0.262
PEER3 0.112 0.289
Table 8.2, page 289
Model A
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 ;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
[alc1-alc3@0];
[level trend];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 0.048
Degrees of Freedom 1
P-Value 0.8262
Chi-Square Test of Model Fit for the Baseline Model
Value 736.696
Degrees of Freedom 3
P-Value 0.0000
CFI/TLI
CFI 1.000
TLI 1.004
Loglikelihood
H0 Value -1280.854
H1 Value -1280.830
Information Criteria
Number of Free Parameters 8
Akaike (AIC) 2577.707
Bayesian (BIC) 2617.890
Sample-Size Adjusted BIC 2592.480
(n* = (n + 2) / 24)
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.048
Probability RMSEA <= .05 0.956
SRMR (Standardized Root Mean Square Residual)
Value 0.001
MODEL RESULTS
Estimates S.E. Est./S.E.
LEVEL BY
ALC1 1.000 0.000 0.000
ALC2 1.000 0.000 0.000
ALC3 1.000 0.000 0.000
TREND BY
ALC1 0.000 0.000 0.000
ALC2 0.750 0.000 0.000
ALC3 1.750 0.000 0.000
TREND WITH
LEVEL -0.012 0.005 -2.727
Means
LEVEL 0.226 0.011 21.107
TREND 0.036 0.007 4.898
Intercepts
ALC1 0.000 0.000 0.000
ALC2 0.000 0.000 0.000
ALC3 0.000 0.000 0.000
Variances
LEVEL 0.087 0.007 12.253
TREND 0.020 0.005 3.795
Residual Variances
ALC1 0.048 0.006 7.551
ALC2 0.076 0.004 17.052
ALC3 0.077 0.010 7.756
Model B
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 female;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
[alc1-alc3@0];
level trend on female;
[level trend];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 1.545
Degrees of Freedom 2
P-Value 0.4585
Chi-Square Test of Model Fit for the Baseline Model
Value 742.014
Degrees of Freedom 6
P-Value 0.0000
CFI/TLI
CFI 1.000
TLI 1.002
Loglikelihood
H0 Value -2064.242
H1 Value -2063.470
Information Criteria
Number of Free Parameters 10
Akaike (AIC) 4148.485
Bayesian (BIC) 4198.714
Sample-Size Adjusted BIC 4166.951
(n* = (n + 2) / 24)
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.055
Probability RMSEA <= .05 0.924
SRMR (Standardized Root Mean Square Residual)
Value 0.007
MODEL RESULTS
Estimates S.E. Est./S.E. Std StdYX
LEVEL BY
ALC1 1.000 0.000 0.000 0.295 0.800
ALC2 1.000 0.000 0.000 0.295 0.748
ALC3 1.000 0.000 0.000 0.295 0.693
TREND BY
ALC1 0.000 0.000 0.000 0.000 0.000
ALC2 0.750 0.000 0.000 0.105 0.266
ALC3 1.750 0.000 0.000 0.244 0.575
LEVEL ON
FEMALE -0.042 0.022 -1.914 -0.142 -0.069
TREND ON
FEMALE 0.008 0.015 0.522 0.056 0.027
TREND WITH
LEVEL -0.012 0.005 -2.662 -0.296 -0.296
Intercepts
ALC1 0.000 0.000 0.000 0.000 0.000
ALC2 0.000 0.000 0.000 0.000 0.000
ALC3 0.000 0.000 0.000 0.000 0.000
LEVEL 0.251 0.017 14.661 0.853 0.853
TREND 0.031 0.012 2.641 0.223 0.223
Residual Variances
ALC1 0.049 0.006 7.621 0.049 0.360
ALC2 0.075 0.004 17.042 0.075 0.488
ALC3 0.077 0.010 7.794 0.077 0.427
LEVEL 0.086 0.007 12.194 0.995 0.995
TREND 0.019 0.005 3.742 0.999 0.999
R-SQUARE
Observed
Variable R-Square
ALC1 0.640
ALC2 0.512
ALC3 0.573
Latent
Variable R-Square
LEVEL 0.005
TREND 0.001
Baseline model to be compared with for model B
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 female;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
[alc1-alc3@0];
level trend on female@0;
[level trend];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 5.367
Degrees of Freedom 4
P-Value 0.2512
Model C
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 female;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
[alc1-alc3@0];
level on female;
trend on female@0;
[level trend];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 1.817
Degrees of Freedom 3
P-Value 0.6103
Chi-Square Test of Model Fit for the Baseline Model
Value 742.014
Degrees of Freedom 6
P-Value 0.0000
CFI/TLI
CFI 1.000
TLI 1.003
Loglikelihood
H0 Value -2064.379
H1 Value -2063.470
Information Criteria
Number of Free Parameters 9
Akaike (AIC) 4146.758
Bayesian (BIC) 4191.963
Sample-Size Adjusted BIC 4163.377
(n* = (n + 2) / 24)
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.042
Probability RMSEA <= .05 0.981
SRMR (Standardized Root Mean Square Residual)
Value 0.008
MODEL RESULTS
Estimates S.E. Est./S.E.
LEVEL BY
ALC1 1.000 0.000 0.000
ALC2 1.000 0.000 0.000
ALC3 1.000 0.000 0.000
TREND BY
ALC1 0.000 0.000 0.000
ALC2 0.750 0.000 0.000
ALC3 1.750 0.000 0.000
LEVEL ON
FEMALE -0.037 0.019 -1.887
TREND ON
FEMALE 0.000 0.000 0.000
TREND WITH
LEVEL -0.012 0.005 -2.668
Intercepts
ALC1 0.000 0.000 0.000
ALC2 0.000 0.000 0.000
ALC3 0.000 0.000 0.000
LEVEL 0.248 0.016 15.533
TREND 0.036 0.007 4.898
Residual Variances
ALC1 0.049 0.006 7.613
ALC2 0.075 0.004 17.041
ALC3 0.077 0.010 7.804
LEVEL 0.086 0.007 12.198
TREND 0.019 0.005 3.741
Model D
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 peer1 peer2 peer3;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
levelp by peer1 - peer3@1;
trendp by peer1@0 peer2@.75 peer3@1.75;
level on levelp*.8 trendp*.08;
trend on levelp*-.1 trendp*.6;
[alc1-alc3@0];
[peer1-peer3@0];
alc1 with peer1;
alc2 with peer2;
alc3 with peer3;
[level trend];
[levelp trendp];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 11.557
Degrees of Freedom 4
P-Value 0.0209
Chi-Square Test of Model Fit for the Baseline Model
Value 1926.612
Degrees of Freedom 15
P-Value 0.0000
CFI/TLI
CFI 0.996
TLI 0.985
Loglikelihood
H0 Value -3037.266
H1 Value -3031.487
Information Criteria
Number of Free Parameters 23
Akaike (AIC) 6120.532
Bayesian (BIC) 6236.058
Sample-Size Adjusted BIC 6163.004
(n* = (n + 2) / 24)
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.041
90 Percent C.I. 0.014 0.070
Probability RMSEA <= .05 0.656
SRMR (Standardized Root Mean Square Residual)
Value 0.016
MODEL RESULTS
Estimates S.E. Est./S.E.
LEVEL BY
ALC1 1.000 0.000 0.000
ALC2 1.000 0.000 0.000
ALC3 1.000 0.000 0.000
TREND BY
ALC1 0.000 0.000 0.000
ALC2 0.750 0.000 0.000
ALC3 1.750 0.000 0.000
LEVELP BY
PEER1 1.000 0.000 0.000
PEER2 1.000 0.000 0.000
PEER3 1.000 0.000 0.000
TRENDP BY
PEER1 0.000 0.000 0.000
PEER2 0.750 0.000 0.000
PEER3 1.750 0.000 0.000
LEVEL ON
LEVELP 0.799 0.102 7.810
TRENDP 0.080 0.182 0.441
TREND ON
LEVELP -0.143 0.076 -1.888
TRENDP 0.577 0.192 3.002
TREND WITH
LEVEL -0.006 0.005 -1.252
TRENDP WITH
LEVELP 0.001 0.007 0.167
ALC1 WITH
PEER1 0.011 0.006 1.785
ALC2 WITH
PEER2 0.034 0.005 7.310
ALC3 WITH
PEER3 0.037 0.010 3.678
Means
LEVELP 0.188 0.012 15.795
TRENDP 0.096 0.010 9.956
Intercepts
ALC1 0.000 0.000 0.000
ALC2 0.000 0.000 0.000
ALC3 0.000 0.000 0.000
PEER1 0.000 0.000 0.000
PEER2 0.000 0.000 0.000
PEER3 0.000 0.000 0.000
LEVEL 0.067 0.016 4.272
TREND 0.008 0.015 0.572
Variances
LEVELP 0.070 0.010 6.735
TRENDP 0.028 0.009 3.224
Residual Variances
ALC1 0.048 0.006 7.560
ALC2 0.076 0.004 17.235
ALC3 0.076 0.010 7.831
PEER1 0.106 0.011 9.850
PEER2 0.171 0.009 19.656
PEER3 0.129 0.018 7.355
LEVEL 0.042 0.007 5.671
TREND 0.009 0.005 1.702
Baseline model for comparing with model D
TITLE:
alcohol2.inp
Linear growth model
DATA:
File is d:aldaatsdataasciihttps://stats.idre.ucla.edu/wp-content/uploads/2016/02/alcohol2-1.txt;
VARIABLE:
Names are ID FEMALE ALC1 ALC2 ALC3 PEER1 PEER2 PEER3;
Missing are all(999);
Usevariables are alc1 alc2 alc3 peer1 peer2 peer3;
ANALYSIS:
Type = meanstructure;
MODEL:
level by alc1 - alc3@1;
trend by alc1@0 alc2@.75 alc3@1.75;
levelp by peer1 - peer3@1;
trendp by peer1@0 peer2@.75 peer3@1.75;
level on levelp@0 trendp@0;
trend on levelp@0 trendp@0;
[alc1-alc3@0];
[peer1-peer3@0];
alc1 with peer1;
alc2 with peer2;
alc3 with peer3;
[level trend];
[levelp trendp];
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 342.648
Degrees of Freedom 8
P-Value 0.0000