Results: JobSatisfaction.sas

Personality, Job Satisfaction and Performance

Look at the adjusted sample covariance matrix

The PRINT Procedure

Data Set WORK.ADJUSTED

Obs _type_ _name_ Extra Neuro ITQ Satis Perf
1 cov Extra 22.739 -7.370 -4.480 15.350 2.570
2 cov Neuro -7.370 8.596 7.250 -8.550 -1.810
3 cov ITQ -4.480 7.250 53.664 -45.960 -5.780
4 cov Satis 15.350 -8.550 -45.960 112.061 16.500
5 cov Perf 2.570 -1.810 -5.780 16.500 31.964
6 n   724.000 724.000 724.000 724.000 724.000

Personality, Job Satisfaction and Performance

Covariance matrix adjusted for measurement error

The CALIS Procedure

Covariance Structure Analysis: Model and Initial Values

The CALIS Procedure

Modeling Specification

Modeling Info

Modeling Information
Maximum Likelihood Estimation
Data Set WORK.ADJUSTED
N Obs 724
Model Type LINEQS
Analysis Covariances

Optimization

Personality, Job Satisfaction and Performance

Covariance matrix adjusted for measurement error

The CALIS Procedure

Covariance Structure Analysis: Optimization

Levenberg-Marquardt Optimization

Scaling Update of More (1978)

Optimization Problem

Parameter Estimates 15
Functions (Observations) 15
Lower Bounds 5
Upper Bounds 0

Iteration Start

Optimization Start
Active Constraints 0 Objective Function 4.4155012E-6
Max Abs Gradient Element 0.0036932583 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 4.416E-6 1.5E-7 0 1.000

Iteration Stop

Optimization Results
Iterations 1 Function Calls 7
Jacobian Calls 3 Active Constraints 0
Objective Function 0 Max Abs Gradient Element 1.4996302E-7
Lambda 0 Actual Over Pred Change 1.0000022079
Radius 0.0059433939    
Convergence criterion (GCONV2=0) satisfied.

Personality, Job Satisfaction and Performance

Covariance matrix adjusted for measurement error

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

Fit

Fit Summary

Fit Summary
Chi-Square 0.0000
Chi-Square DF 0
Pr > Chi-Square .

Personality, Job Satisfaction and Performance

Covariance matrix adjusted for measurement error

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

ML Estimation

Equations

Linear Equations
Satis =   0.4884 (**) Extra + -0.5760 (**) Neuro + 1.0000   epsilon1        
Perf =   -0.00761 (ns) Extra + -0.0753 (ns) Neuro + 0.1425 (**) Satis + 1.0000   epsilon2
ITQ =   0.2998 (**) Extra + 0.7052 (**) Neuro + -0.3974 (**) Satis + 1.0000   epsilon3

Linear Effects

Effects in Linear Equations
Variable Predictor Parameter Estimate Standard
Error		 t Value Pr > |t|
Satis Extra gamma1 0.48837 0.09155 5.3345 <.0001
Satis Neuro gamma2 -0.57596 0.14891 -3.8679 0.0001
Perf Extra gamma3 -0.00761 0.05078 -0.1498 0.8809
Perf Neuro gamma4 -0.07532 0.08185 -0.9202 0.3575
Perf Satis beta1 0.14254 0.02022 7.0491 <.0001
ITQ Extra gamma5 0.29982 0.05259 5.7015 <.0001
ITQ Neuro gamma6 0.70524 0.08476 8.3205 <.0001
ITQ Satis beta2 -0.39739 0.02094 -18.9783 <.0001

Variance Parms

Estimates for Variances of Exogenous Variables
Variable
Type		 Variable Parameter Estimate Standard
Error		 t Value Pr > |t|
Observed Extra phi11 22.73920 1.19515 19.0263 <.0001
  Neuro phi22 8.59560 0.45177 19.0263 <.0001
Error epsilon1 psi1 99.64025 5.23698 19.0263 <.0001
  epsilon2 psi2 29.49591 1.55027 19.0263 <.0001
  epsilon3 psi3 31.63000 1.66244 19.0263 <.0001

Covariance Parms

Covariances Among Exogenous Variables
Var1 Var2 Parameter Estimate Standard
Error		 t Value Pr > |t|
Extra Neuro phi12 -7.37000 0.58736 -12.5477 <.0001
epsilon2 epsilon3 psi23 1.28295 1.13617 1.1292 0.2588

Sq. Mult. Correlations

Squared Multiple Correlations
Variable Error Variance Total Variance R-Square
Satis 99.64025 112.06120 0.1108
Perf 29.49591 31.96453 0.0772
ITQ 31.63000 53.66400 0.4106

Personality, Job Satisfaction and Performance

Surface path analysis of unadjusted covariance matrix

The CALIS Procedure

Covariance Structure Analysis: Model and Initial Values

The CALIS Procedure

Modeling Specification

Modeling Info

Modeling Information
Maximum Likelihood Estimation
Data Set WORK.SIGMAHAT
N Obs 724
Model Type LINEQS
Analysis Covariances

Optimization

Personality, Job Satisfaction and Performance

Surface path analysis of unadjusted covariance matrix

The CALIS Procedure

Covariance Structure Analysis: Optimization

Levenberg-Marquardt Optimization

Scaling Update of More (1978)

Optimization Problem

Parameter Estimates 15
Functions (Observations) 15
Lower Bounds 5
Upper Bounds 0

Iteration Start

Optimization Start
Active Constraints 0 Objective Function 0
Max Abs Gradient Element 2.841759E-16 Radius 1

Iteration Stop

Optimization Results
Iterations 0 Function Calls 4
Jacobian Calls 1 Active Constraints 0
Objective Function 0 Max Abs Gradient Element 2.841759E-16
Lambda 0 Actual Over Pred Change 0
Radius 1    
Convergence criterion (ABSGCONV=0.00001) satisfied.

Personality, Job Satisfaction and Performance

Surface path analysis of unadjusted covariance matrix

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

Fit

Fit Summary

Fit Summary
Chi-Square 0.0000
Chi-Square DF 0
Pr > Chi-Square .

Personality, Job Satisfaction and Performance

Surface path analysis of unadjusted covariance matrix

The CALIS Procedure

Covariance Structure Analysis: Maximum Likelihood Estimation

ML Estimation

Equations

Linear Equations
Satis =   0.4227 (**) Extra + -0.3667 (**) Neuro + 1.0000   epsilon1        
Perf =   0.0145 (ns) Extra + -0.0479 (ns) Neuro + 0.1161 (**) Satis + 1.0000   epsilon2
ITQ =   0.1045 (**) Extra + 0.3531 (**) Neuro + -0.3260 (**) Satis + 1.0000   epsilon3

Linear Effects

Effects in Linear Equations
Variable Predictor Parameter Estimate Standard
Error		 t Value Pr > |t|
Satis Extra gamma1 0.42271 0.08175 5.1707 <.0001
Satis Neuro gamma2 -0.36671 0.11616 -3.1570 0.0016
Perf Extra gamma3 0.01452 0.05694 0.2551 0.7987
Perf Neuro gamma4 -0.04792 0.07999 -0.5991 0.5491
Perf Satis beta1 0.11611 0.02542 4.5676 <.0001
ITQ Extra gamma5 0.10447 0.05223 2.0002 0.0455
ITQ Neuro gamma6 0.35311 0.07338 4.8122 <.0001
ITQ Satis beta2 -0.32595 0.02332 -13.9788 <.0001

Variance Parms

Estimates for Variances of Exogenous Variables
Variable
Type		 Variable Parameter Estimate Standard
Error		 t Value Pr > |t|
Observed Extra phi11 29.92000 1.57256 19.0263 <.0001
  Neuro phi22 14.82000 0.77892 19.0263 <.0001
Error epsilon1 psi1 127.03609 6.67687 19.0263 <.0001
  epsilon2 psi2 59.43015 3.12358 19.0263 <.0001
  epsilon3 psi3 50.00726 2.62832 19.0263 <.0001

Covariance Parms

Covariances Among Exogenous Variables
Var1 Var2 Parameter Estimate Standard
Error		 t Value Pr > |t|
Extra Neuro phi12 -7.37000 0.82914 -8.8887 <.0001
epsilon2 epsilon3 psi23 -0.03116 2.02605 -0.0154 0.9877

Sq. Mult. Correlations

Squared Multiple Correlations
Variable Error Variance Total Variance R-Square
Satis 127.03609 136.66000 0.0704
Perf 59.43015 61.47000 0.0332
ITQ 50.00726 67.08000 0.2545