Results: Diversity3.sas

Diversity study: Test sex differences with a standardized latent model

Combined data: Match fit chi-square = 59.7243

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

The CALIS Procedure

Fit

Fit Summary

Fit Summary
Chi-Square 59.7243
Chi-Square DF 50
Pr > Chi-Square 0.1632

Diversity study: Test sex differences with a standardized latent model

Full 2-group FA Model: All parameters different for M and F

Compare chisq = 118.1198, df=100, p = 0.1043

The CALIS Procedure

Covariance Structure Analysis: Models and Initial Values

The CALIS Procedure

Modeling Specification

Modeling Info

Modeling Information
Maximum Likelihood Estimation
Group Label Data Set Data Records N Obs Model Type Analysis
N Read N Used
1 Males WORK.BOYS 173 173 173 Model 1 LINEQS Covariances
2 Females WORK.GIRLS 125 125 125 Model 2 LINEQS Covariances

Optimization

Diversity study: Test sex differences with a standardized latent model

Full 2-group FA Model: All parameters different for M and F

Compare chisq = 118.1198, df=100, p = 0.1043

The CALIS Procedure

Covariance Structure Analysis: Optimization

Levenberg-Marquardt Optimization

Scaling Update of More (1978)

Optimization Problem

Parameter Estimates 82
Functions (Observations) 182
Lower Bounds 26
Upper Bounds 0

Iteration Start

Optimization Start
Active Constraints 0 Objective Function 0.5719831826
Max Abs Gradient Element 0.3836898016 Radius 1

Iteration History

Iteration   Restarts Function
Calls		 Active
Constraints		   Objective
Function		 Objective
Function
Change		 Max Abs
Gradient
Element		 Lambda Ratio
Between
Actual
and
Predicted
Change
1   0 4 0   0.42887 0.1431 0.1152 0.0318 0.825
2   0 6 0   0.39807 0.0308 0.0262 0 1.223
3   0 8 0   0.39650 0.00156 0.00696 0 1.146
4   0 10 0   0.39639 0.000116 0.00196 0 1.045
5   0 12 0   0.39638 0.000010 0.000670 0 0.896
6   0 14 0   0.39638 1.173E-6 0.000407 0 0.757
7   0 16 0   0.39638 1.728E-7 0.000149 0 0.671
8   0 18 0   0.39638 3.008E-8 0.000084 0 0.628
9   0 20 0   0.39638 5.683E-9 0.000032 0 0.607
10   0 22 0   0.39638 1.115E-9 0.000017 0 0.596

Iteration Stop

Optimization Results
Iterations 10 Function Calls 25
Jacobian Calls 12 Active Constraints 0
Objective Function 0.3963752641 Max Abs Gradient Element 0.000017209
Lambda 0 Actual Over Pred Change 0.5958738168
Radius 0.0003482869    
Convergence criterion (GCONV=1E-8) satisfied.

Diversity study: Test sex differences with a standardized latent model

Full 2-group FA Model: All parameters different for M and F

Compare chisq = 118.1198, df=100, p = 0.1043

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

Fit

Fit Summary

Fit Summary
Chi-Square 118.1198
Chi-Square DF 100
Pr > Chi-Square 0.1043

Diversity study: Test sex differences with a standardized latent model

Full 2-group FA Model: All parameters different for M and F

Compare chisq = 118.1198, df=100, p = 0.1043

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

ML Estimation

Model 1

Equations

Model 1. Linear Equations
commit1 =   2.9344 (**) Fcommit + 1.0000   e1
commit2 =   2.9325 (**) Fcommit + 1.0000   e2
relcoll1 =   1.7854 (**) Frelcoll + 1.0000   e3
relcoll2 =   1.4776 (**) Frelcoll + 1.0000   e4
relman1 =   5.4915 (**) Frelman + 1.0000   e5
relman2 =   5.5263 (**) Frelman + 1.0000   e6
fairad1 =   2.6088 (**) Ffairad + 1.0000   e7
fairad2 =   2.4034 (**) Ffairad + 1.0000   e8
csat1 =   1.8193 (**) Fcsat + 1.0000   e9
csat2 =   1.8367 (**) Fcsat + 1.0000   e10
SM1 =   1.1427 (**) FSM + 1.0000   e11
SM2 =   1.1181 (**) FSM + 1.0000   e12
SM3 =   1.0440 (**) FSM + 1.0000   e13

Linear Effects

Model 1. Effects in Linear Equations
Variable Predictor Parameter Estimate Standard
Error		 t Value Pr > |t|
commit1 Fcommit blambda1 2.93438 0.20758 14.1364 <.0001
commit2 Fcommit blambda2 2.93248 0.22972 12.7656 <.0001
relcoll1 Frelcoll blambda3 1.78536 0.15081 11.8387 <.0001
relcoll2 Frelcoll blambda4 1.47764 0.13507 10.9401 <.0001
relman1 Frelman blambda5 5.49153 0.36366 15.1009 <.0001
relman2 Frelman blambda6 5.52625 0.32594 16.9546 <.0001
fairad1 Ffairad blambda7 2.60879 0.17781 14.6719 <.0001
fairad2 Ffairad blambda8 2.40337 0.19022 12.6347 <.0001
csat1 Fcsat blambda9 1.81932 0.13847 13.1388 <.0001
csat2 Fcsat blambda10 1.83668 0.12211 15.0415 <.0001
SM1 FSM blambda11 1.14265 0.09638 11.8561 <.0001
SM2 FSM blambda12 1.11813 0.09352 11.9560 <.0001
SM3 FSM blambda13 1.04397 0.12016 8.6884 <.0001

Variance Parms

Model 1. Estimates for Variances of Exogenous Variables
Variable
Type		 Variable Parameter Estimate Standard
Error		 t Value Pr > |t|
Latent Fcommit   1.00000      
  Frelcoll   1.00000      
  Frelman   1.00000      
  Ffairad   1.00000      
  Fcsat   1.00000      
  FSM   1.00000      
Error e1 bomega01 1.78464 0.55536 3.2135 0.0013
  e2 bomega02 3.46699 0.64020 5.4155 <.0001
  e3 bomega03 1.42133 0.30185 4.7087 <.0001
  e4 bomega04 1.43456 0.23576 6.0847 <.0001
  e5 bomega05 6.73797 1.12490 5.9899 <.0001
  e6 bomega06 2.03425 0.89849 2.2641 0.0236
  e7 bomega07 1.43216 0.35150 4.0744 <.0001
  e8 bomega08 2.83317 0.40585 6.9808 <.0001
  e9 bomega09 1.24631 0.22311 5.5860 <.0001
  e10 bomega10 0.46898 0.18867 2.4857 0.0129
  e11 bomega11 0.57921 0.12327 4.6987 <.0001
  e12 bomega12 0.52961 0.11662 4.5412 <.0001
  e13 bomega13 1.58050 0.19560 8.0803 <.0001

Covariance Parms

Model 1. Covariances Among Exogenous Variables
Var1 Var2 Parameter Estimate Standard
Error		 t Value Pr > |t|
Fcommit Frelcoll bc01 0.56795 0.06823 8.3238 <.0001
Fcommit Frelman bc02 0.70072 0.04720 14.8450 <.0001
Frelcoll Frelman bc03 0.74659 0.04822 15.4833 <.0001
Fcommit Ffairad bc04 0.68624 0.05290 12.9723 <.0001
Frelcoll Ffairad bc05 0.65515 0.06135 10.6793 <.0001
Frelman Ffairad bc06 0.79499 0.03781 21.0258 <.0001
Fcommit Fcsat bc07 0.55626 0.06259 8.8873 <.0001
Frelcoll Fcsat bc08 0.57492 0.06628 8.6741 <.0001
Frelman Fcsat bc09 0.63431 0.05233 12.1202 <.0001
Ffairad Fcsat bc10 0.74924 0.04548 16.4755 <.0001
Fcommit FSM bc11 0.36390 0.07863 4.6281 <.0001
Frelcoll FSM bc12 0.23917 0.08910 2.6842 0.0073
Frelman FSM bc13 0.38086 0.07418 5.1341 <.0001
Ffairad FSM bc14 0.36494 0.07898 4.6205 <.0001
Fcsat FSM bc15 0.34198 0.07839 4.3628 <.0001

Sq. Mult. Correlations

Model 1. Squared Multiple Correlations
Variable Error Variance Total Variance R-Square
commit1 1.78464 10.39520 0.8283
commit2 3.46699 12.06642 0.7127
relcoll1 1.42133 4.60884 0.6916
relcoll2 1.43456 3.61796 0.6035
relman1 6.73797 36.89485 0.8174
relman2 2.03425 32.57369 0.9375
fairad1 1.43216 8.23796 0.8262
fairad2 2.83317 8.60938 0.6709
csat1 1.24631 4.55625 0.7265
csat2 0.46898 3.84236 0.8779
SM1 0.57921 1.88486 0.6927
SM2 0.52961 1.77981 0.7024
SM3 1.58050 2.67039 0.4081

Model 2

Equations

Model 2. Linear Equations
commit1 =   3.1597 (**) Fcommit + 1.0000   e1
commit2 =   3.1057 (**) Fcommit + 1.0000   e2
relcoll1 =   1.5310 (**) Frelcoll + 1.0000   e3
relcoll2 =   1.4996 (**) Frelcoll + 1.0000   e4
relman1 =   4.7744 (**) Frelman + 1.0000   e5
relman2 =   4.8337 (**) Frelman + 1.0000   e6
fairad1 =   2.0265 (**) Ffairad + 1.0000   e7
fairad2 =   1.8275 (**) Ffairad + 1.0000   e8
csat1 =   1.6958 (**) Fcsat + 1.0000   e9
csat2 =   1.5373 (**) Fcsat + 1.0000   e10
SM1 =   1.4297 (**) FSM + 1.0000   e11
SM2 =   1.0784 (**) FSM + 1.0000   e12
SM3 =   1.2406 (**) FSM + 1.0000   e13

Linear Effects

Model 2. Effects in Linear Equations
Variable Predictor Parameter Estimate Standard
Error		 t Value Pr > |t|
commit1 Fcommit glambda1 3.15968 0.28830 10.9598 <.0001
commit2 Fcommit glambda2 3.10569 0.29273 10.6096 <.0001
relcoll1 Frelcoll glambda3 1.53097 0.19481 7.8589 <.0001
relcoll2 Frelcoll glambda4 1.49962 0.17130 8.7542 <.0001
relman1 Frelman glambda5 4.77442 0.38801 12.3048 <.0001
relman2 Frelman glambda6 4.83370 0.36569 13.2180 <.0001
fairad1 Ffairad glambda7 2.02645 0.19739 10.2660 <.0001
fairad2 Ffairad glambda8 1.82751 0.21025 8.6921 <.0001
csat1 Fcsat glambda9 1.69576 0.16130 10.5133 <.0001
csat2 Fcsat glambda10 1.53728 0.14459 10.6322 <.0001
SM1 FSM glambda11 1.42966 0.10452 13.6787 <.0001
SM2 FSM glambda12 1.07839 0.10032 10.7498 <.0001
SM3 FSM glambda13 1.24062 0.12649 9.8084 <.0001

Variance Parms

Model 2. Estimates for Variances of Exogenous Variables
Variable
Type		 Variable Parameter Estimate Standard
Error		 t Value Pr > |t|
Latent Fcommit   1.00000      
  Frelcoll   1.00000      
  Frelman   1.00000      
  Ffairad   1.00000      
  Fcsat   1.00000      
  FSM   1.00000      
Error e1 gomega01 1.85679 1.08919 1.7047 0.0882
  e2 gomega02 2.46759 1.07389 2.2978 0.0216
  e3 gomega03 1.39796 0.44081 3.1714 0.0015
  e4 gomega04 0.45795 0.39173 1.1691 0.2424
  e5 gomega05 4.87254 1.49644 3.2561 0.0011
  e6 gomega06 2.42097 1.43085 1.6920 0.0907
  e7 gomega07 1.79199 0.43141 4.1538 <.0001
  e8 gomega08 3.02181 0.48500 6.2306 <.0001
  e9 gomega09 1.15551 0.28633 4.0356 <.0001
  e10 gomega10 0.89016 0.23156 3.8442 0.0001
  e11 gomega11 0.14780 0.11468 1.2889 0.1974
  e12 gomega12 0.56354 0.09635 5.8488 <.0001
  e13 gomega13 1.07846 0.16151 6.6774 <.0001

Covariance Parms

Model 2. Covariances Among Exogenous Variables
Var1 Var2 Parameter Estimate Standard
Error		 t Value Pr > |t|
Fcommit Frelcoll gc01 0.24325 0.09639 2.5235 0.0116
Fcommit Frelman gc02 0.18878 0.09424 2.0033 0.0451
Frelcoll Frelman gc03 0.36782 0.08880 4.1419 <.0001
Fcommit Ffairad gc04 0.47947 0.08791 5.4541 <.0001
Frelcoll Ffairad gc05 0.41514 0.09640 4.3063 <.0001
Frelman Ffairad gc06 0.68970 0.06638 10.3896 <.0001
Fcommit Fcsat gc07 0.43709 0.08630 5.0650 <.0001
Frelcoll Fcsat gc08 0.34585 0.09564 3.6161 0.0003
Frelman Fcsat gc09 0.54682 0.07521 7.2709 <.0001
Ffairad Fcsat gc10 0.73444 0.06801 10.7984 <.0001
Fcommit FSM gc11 0.18913 0.09371 2.0183 0.0436
Frelcoll FSM gc12 0.14361 0.09712 1.4786 0.1392
Frelman FSM gc13 0.15782 0.09298 1.6974 0.0896
Ffairad FSM gc14 0.31197 0.09654 3.2316 0.0012
Fcsat FSM gc15 0.07130 0.10009 0.7123 0.4763

Sq. Mult. Correlations

Model 2. Squared Multiple Correlations
Variable Error Variance Total Variance R-Square
commit1 1.85679 11.84038 0.8432
commit2 2.46759 12.11290 0.7963
relcoll1 1.39796 3.74182 0.6264
relcoll2 0.45795 2.70682 0.8308
relman1 4.87254 27.66758 0.8239
relman2 2.42097 25.78560 0.9061
fairad1 1.79199 5.89850 0.6962
fairad2 3.02181 6.36160 0.5250
csat1 1.15551 4.03110 0.7134
csat2 0.89016 3.25338 0.7264
SM1 0.14780 2.19174 0.9326
SM2 0.56354 1.72646 0.6736
SM3 1.07846 2.61760 0.5880

Simultaneous Tests

Simultaneous Tests
Simultaneous
Test		 Parametric
Function		 Function
Value		 DF Chi-Square p Value
SexDiffCorr     15 41.85710 0.0002
  FcommitFrelcoll 0.32470 1 7.55932 0.0060
  FcommitFrelman 0.51194 1 23.59289 <.0001
  FrelcollFrelman 0.37877 1 14.04990 0.0002
  FcommitFfairad 0.20677 1 4.06140 0.0439
  FrelcollFfairad 0.24001 1 4.41178 0.0357
  FrelmanFfairad 0.10530 1 1.89967 0.1681
  FcommitFcsat 0.11917 1 1.24950 0.2636
  FrelcollFcsat 0.22907 1 3.87517 0.0490
  FrelmanFcsat 0.08748 1 0.91167 0.3397
  FfairadFcsat 0.01480 1 0.03271 0.8565
  FcommitFSM 0.17477 1 2.04135 0.1531
  FrelcollFSM 0.09556 1 0.52567 0.4684
  FrelmanFSM 0.22304 1 3.51613 0.0608
  FfairadFSM 0.05297 1 0.18035 0.6711
  FcsatFSM 0.27068 1 4.53309 0.0332

Diversity study: Test sex differences with a standardized latent model

Reduced Model: Inter-factor correlations equal for M and F

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

The CALIS Procedure

Fit

Fit Summary

Fit Summary
Chi-Square 161.6637
Chi-Square DF 115
Pr > Chi-Square 0.0027

Diversity study: Test sex differences with a standardized latent model

Likelihood ratio test of H0: Factor correlations equal for M and F

The IML Procedure

Gsq_pvalue

Gsq pvalue
43.5439 0.0001296