Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010 10:57 PM
INPUT INSTRUCTIONS
! SCRIPT NAME : rawVC3b (dp)
! GOAL : To evaluate whether different genes are important for males and fe
! DATA : continuous
! INPUT : raw data
! UNI/BI/MULTI : uni
! DATA-GROUPS : MZM DZM MZF DZF DOSMF DOSFM
! MEANS MODEL : grand mean, age effect, sex effect
! VARIANCE COVARIANCE MODEL(S) : 1.ADE males + ADE females + DOS A/D-correlation is
! : 2.ADE males = ADE females + DOS A/D-correlation is not
! : 3.ADE males = ADE females + DOS A-correlation = DZ A-co
data: file is example.dat;
variable:
names are country famid zygos sex1 age1 height1 weight1 bmi1
sex2 age2 height2 weight2 bmi2;
usevar are bmi1 sex1 age1 bmi2 sex2 age2;
grouping=zygos(1=MZM 2=DZM 3=MZF 4=DZF 5=DOSMF 6=DOSFM); ! specify the groups
missing=all(-1); ! specify missing data symbol
model :
bmi1 on sex1 (b1)
age1 (b2);
bmi2 on sex2 (b1)
age2 (b2);
[bmi1 bmi2] (m);
model MZM :
bmi1 bmi2 (mv);
bmi1 with bmi2 (mc1);
model DZM :
bmi1 bmi2 (mv);
bmi1 with bmi2 (mc2);
model MZF :
bmi1 bmi2 (fv);
bmi1 with bmi2 (fc1);
model DZF :
bmi1 bmi2 (fv);
bmi1 with bmi2 (fc2);
model DOSMF :
bmi1 (mv); bmi2 (fv);
bmi1 with bmi2 (mfc);
model DOSFM :
bmi1 (fv); bmi2 (mv);
bmi1 with bmi2 (mfc);
model constraint:
new(ma md me mx mw mz);
ma=mx*mx;
md=mw*mw;
me=mz*mz;
mv=ma+md+me;
mc1=ma+md;
mc2=0.5*ma+0.25*md;
new(fa fd fe fx fw fz);
fa=fx*fx;
fd=fw*fw;
fe=fz*fz;
fv=fa+fd+fe;
fc1=fa+fd;
fc2=0.5*fa+0.25*fd;
new(f*0.1 j*0.1); j>0; j<0.25;
mfc=f*mx*fx+j*mw*fw; ! f and j can not be identified simultaniously
! in this example they will get fixed at their boundaries
f=0.5; ! we fix this parameter to identify the model
! Uncomment for Model ADE with all components equal
! ma=fa;
! md=fd;
! me=fe;
! Uncomment for Model ACE with all components equal and DOS correlations = DZ correlations
! ma=fa;
! md=fd;
! me=fe;
! f=0.5;
! j=0.25
*** WARNING
Input line exceeded 90 characters. Some input may be truncated.
! GOAL : To evaluate whether different genes are important for males and females, ADE mode
*** WARNING
Data set contains cases with missing on all variables except
x-variables. These cases were not included in the analysis.
Number of cases with missing on all variables except x-variables: 3
2 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
SUMMARY OF ANALYSIS
Number of groups 6
Number of observations
Group MZM 61
Group DZM 39
Group MZF 77
Group DZF 67
Group DOSMF 36
Group DOSFM 24
Number of dependent variables 2
Number of independent variables 4
Number of continuous latent variables 0
Observed dependent variables
Continuous
BMI1 BMI2
Observed independent variables
SEX1 AGE1 SEX2 AGE2
Variables with special functions
Grouping variable ZYGOS
Estimator ML
Information matrix OBSERVED
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
Maximum number of iterations for H1 2000
Convergence criterion for H1 0.100D-03
Input data file(s)
example.dat
Input data format FREE
SUMMARY OF DATA
Group MZM
Number of missing data patterns 3
Group DZM
Number of missing data patterns 3
Group MZF
Number of missing data patterns 3
Group DZF
Number of missing data patterns 3
Group DOSMF
Number of missing data patterns 3
Group DOSFM
Number of missing data patterns 3
COVARIANCE COVERAGE OF DATA
Minimum covariance coverage value 0.100
PROPORTION OF DATA PRESENT FOR MZM
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.902
BMI2 0.852 0.951
SEX1 0.902 0.951 1.000
AGE1 0.902 0.951 1.000 1.000
SEX2 0.902 0.951 1.000 1.000 1.000
AGE2 0.902 0.951 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
PROPORTION OF DATA PRESENT FOR DZM
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.897
BMI2 0.744 0.846
SEX1 0.897 0.846 1.000
AGE1 0.897 0.846 1.000 1.000
SEX2 0.897 0.846 1.000 1.000 1.000
AGE2 0.897 0.846 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
PROPORTION OF DATA PRESENT FOR MZF
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.961
BMI2 0.922 0.961
SEX1 0.961 0.961 1.000
AGE1 0.961 0.961 1.000 1.000
SEX2 0.961 0.961 1.000 1.000 1.000
AGE2 0.961 0.961 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
PROPORTION OF DATA PRESENT FOR DZF
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.970
BMI2 0.940 0.970
SEX1 0.970 0.970 1.000
AGE1 0.970 0.970 1.000 1.000
SEX2 0.970 0.970 1.000 1.000 1.000
AGE2 0.970 0.970 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
PROPORTION OF DATA PRESENT FOR DOSMF
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.917
BMI2 0.806 0.889
SEX1 0.917 0.889 1.000
AGE1 0.917 0.889 1.000 1.000
SEX2 0.917 0.889 1.000 1.000 1.000
AGE2 0.917 0.889 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
PROPORTION OF DATA PRESENT FOR DOSFM
Covariance Coverage
BMI1 BMI2 SEX1 AGE1 SEX2
________ ________ ________ ________ ________
BMI1 0.958
BMI2 0.792 0.833
SEX1 0.958 0.833 1.000
AGE1 0.958 0.833 1.000 1.000
SEX2 0.958 0.833 1.000 1.000 1.000
AGE2 0.958 0.833 1.000 1.000 1.000
Covariance Coverage
AGE2
________
AGE2 1.000
THE MODEL ESTIMATION TERMINATED NORMALLY
THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES MAY NOT BE
TRUSTWORTHY FOR SOME PARAMETERS DUE TO A NON-POSITIVE DEFINITE
FIRST-ORDER DERIVATIVE PRODUCT MATRIX. THIS MAY BE DUE TO THE STARTING
VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE
CONDITION NUMBER IS 0.260D-10.
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 43.240
Degrees of Freedom 68
P-Value 0.9917
Chi-Square Contributions From Each Group
MZM 14.511
DZM 5.137
MZF 4.337
DZF 9.391
DOSMF 6.051
DOSFM 3.813
Chi-Square Test of Model Fit for the Baseline Model
Value 251.891
Degrees of Freedom 54
P-Value 0.0000
CFI/TLI
CFI 1.000
TLI 1.099
Loglikelihood
H0 Value -3767.415
H1 Value -3745.795
Information Criteria
Number of Free Parameters 10
Akaike (AIC) 7554.831
Bayesian (BIC) 7592.001
Sample-Size Adjusted BIC 7560.286
(n* = (n + 2) / 24)
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.000
Probability RMSEA <= .05 0.999
SRMR (Standardized Root Mean Square Residual)
Value 0.240
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group MZM
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 10.150 1.291 7.862 0.000
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 12.049 1.247 9.665 0.000
BMI2 12.049 1.247 9.665 0.000
Group DZM
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 3.309 1.198 2.762 0.006
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 12.049 1.247 9.665 0.000
BMI2 12.049 1.247 9.665 0.000
Group MZF
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 9.356 1.297 7.215 0.000
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 13.734 1.156 11.881 0.000
BMI2 13.734 1.156 11.881 0.000
Group DZF
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 3.687 1.384 2.663 0.008
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 13.734 1.156 11.881 0.000
BMI2 13.734 1.156 11.881 0.000
Group DOSMF
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 3.362 1.112 3.023 0.003
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 12.049 1.247 9.665 0.000
BMI2 13.734 1.156 11.881 0.000
Group DOSFM
BMI1 ON
SEX1 0.887 0.341 2.603 0.009
AGE1 0.097 0.014 6.973 0.000
BMI2 ON
SEX2 0.887 0.341 2.603 0.009
AGE2 0.097 0.014 6.973 0.000
BMI2 WITH
BMI1 3.362 1.112 3.023 0.003
Intercepts
BMI1 20.203 0.579 34.873 0.000
BMI2 20.203 0.579 34.873 0.000
Residual Variances
BMI1 13.734 1.156 11.881 0.000
BMI2 12.049 1.247 9.665 0.000
New/Additional Parameters
MA 3.085 4.386 0.703 0.482
MD 7.066 4.340 1.628 0.104
ME 1.898 0.377 5.035 0.000
MX 1.756 1.249 1.407 0.160
MW 2.658 0.816 3.256 0.001
MZ 1.378 0.137 10.071 0.000
FA 5.393 5.256 1.026 0.305
FD 3.963 5.287 0.750 0.454
FE 4.378 0.724 6.051 0.000
FX 2.322 1.132 2.052 0.040
FW 1.991 1.328 1.499 0.134
FZ 2.092 0.173 12.102 0.000
F 0.500 0.000 0.000 1.000
J 0.250 0.000 ********* 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.544E-08
(ratio of smallest to largest eigenvalue)
Beginning Time: 22:57:43
Ending Time: 22:57:44
Elapsed Time: 00:00:01
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