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Example 1: A Simple Regression Model on page 15
|
EQS code: manul1.eqs |
SAS code |
/TITLE
STABILITY OF POWERLESSNESS
(EXAMPLE IN EQS MANUAL P.15)
/SPECIFICATIONS
CAS=932; VAR=6; ME=LS;
/EQUATIONS
V4 = 1*V2 - 1*V5 + E4;
/VARIANCES
V2 = 9*; V5 = 9*; E4 = 2*;
/COVARIANCES
V5,V2 = -4*;
/MATRIX
11.834
6.947 9.364
6.819 5.091 12.532
4.783 5.028 7.495 9.986
-3.839 -3.889 -3.841 -3.625 9.610
-2.189 -1.883 -2.175 -1.878 3.552 4.503
/END
|
data power(TYPE=COV);
_type_ = 'cov';
input _name_ $ v1-v6;
datalines;
v1 11.834 . . . . .
v2 6.947 9.364 . . . .
v3 6.819 5.091 12.532 . . .
v4 4.783 5.028 7.495 9.986 . .
v5 -3.839 -3.889 -3.841 -3.625 9.610 .
v6 -2.189 -1.883 -2.175 -1.878 3.552 4.503
;
run;
proc calis cov data = power method = ls nobs = 932 ;
Lineqs
V4 = b1 v2 + b2 v5 + E4;
Std
v2 = ev2(9),
v5 = ev5(9),
e4 = ee4(2);
Cov
v2 v5 = Theta (-4);
run;
|
Example 2: A Two-Equation Path Model on page 22
|
EQS code: manul2.eqs |
SAS code |
/TITLE
PATH ANALYSIS MODEL
(EXAMPLE IN EQS MANUAL P.22)
/SPECIFICATIONS
CAS=932; VAR=6; ME=ML;
/LABEL
V1=ANOMIE67; V2=POWRLS67;
V3=ANOMIE71; V4=POWRLS71;
/EQUATIONS
V3 = 1*V1 + 1*V2 + E3;
V4 = 1*V1 + 1*V2 + E4;
/VARIANCES
V1 TO V2 = 10*;
E3 TO E4 = 2*;
/COVARIANCES
V2,V1= 7*;
/MATRIX
11.834
6.947 9.364
6.819 5.091 12.532
4.783 5.028 7.495 9.986
-3.839 -3.889 -3.841 -3.625 9.610
-2.189 -1.883 -2.175 -1.878 3.552 4.503
/diagram
title='Diagram from Manul2';
orientation=landscape;
border=yes;
tlocation=bottom;
layout= v1 b v3 e3&
v2 b v4 e4;
/end |
/*********************************************
This example uses the same covariance matrix
from the example above.
The labels can be created in a data step
which we omitted here.
********************************************/
proc calis cov data=power method = ml nobs = 932;
Lineqs
v3 = a3 v1 + b3 v2 + e3,
v4 = a4 v1 + b4 v2 + e4;
Std
v1 - v2 = ev1 - ev2,
e3 - e4 = ee3 - ee4;
Cov
v1 v2 = Theta (.7);
run; |
Example 3: A Factor Analysis Model on page 29
|
EQS code: manul3.eqs |
SAS code |
/TITLE
FACTOR ANALYSIS MODEL
(EXAMPLE IN EQS MANUAL P.29)
/SPECIFICATIONS
CAS=932; VAR=6; ME=GLS;
/LABEL
V1=ANOMIA67; V2=POWRLS67;
V3=ANOMIA71; V4=POWRLS71;
/EQUATIONS
V1 = 2*F1 + E1;
V2 = 2*F1 + E2;
V3 = 2*F2 + E3;
V4 = 2*F2 + E4;
/VARIANCES
F1 TO F2 = 1.0;
E1 TO E4 = 3*;
/COVARIANCES
F2,F1= .3*;
e3,e1 = *;
e4,e2 = *;
/MATRIX
11.834
6.947 9.364
6.819 5.091 12.532
4.783 5.028 7.495 9.986
-3.839 -3.889 -3.841 -3.625 9.610
-2.189 -1.883 -2.175 -1.878 3.552 4.503
/constraints
(v1,f1) = (v3,f2);
(v2,f1) = (v4,f2);
(e1,e1) = (e3,e3);
(e2,e2) = (e4,e4);
(e3,e1) = (e4,e2);
/DIAGRAM
title='Diagram from Manul3';
tlocation=bottom;
orientation=landscape;
border=yes;
postscript='MANUL3.PS';
layout=E1 b E2 E3 b E4 &
V1 b V2 V3 b V4 &
b F1 b b F2;
/END
|
/********************************************** This example uses the same covariance matrix as in example 1. *********************************************/ proc calis cov data=power method = gls nobs = 932; lineqs v1 = a1 f1 + e1, v2 = a2 f1 + e2, v3 = a1 f2 + e3, v4 = a2 f2 + e4; std f1- f2 = 1.0, e1 e3 = ee1, e2 e4 = ee2; cov f1 f2 = theta1, e1 e3 = theta2, e2 e4 = theta2; run; |
Example 4: A Complete Latent Variable Model on page 33
|
EQS code: manul4.eqs |
SAS code |
/TITLE A COMPLETE LATENT VARIABLE MODEL (EXAMPLE IN EQS MANUAL P.33) /SPECIFICATIONS CAS=932; VAR=6; ME=ML; MAT=COV; data='MANUL4.DAT'; /LABEL V1=ANOMIA67; V2=POWRLS67; V3=ANOMIA71; V4=POWRLS71; V5=EDUCATON; V6=OCCUPATN; /EQUATIONS V1 = F1 + E1; V2 = .833 F1 + E2; V3 = F2 + E3; V4 = .833 F2 + E4; V5 = F3 + E5; V6 = .5 *F3 + E6; F1 = -.5 *F3 + D1; F2 = .5 *F1 - .5*F3 + D2; /VARIANCES D1 TO D2 = 4*; F3 = 6*; E1 TO E6 = 3*; /COVARIANCES E1,E3 = .2*; E2,E4 = .2*; /CONSTRAINTS (E1,E1) = (E3,E3); (E2,E2) = (E4,E4); (E3,E1) = (E4,E2); /END |
/*********************************************
This example uses the same covariance matrix
as in example 1.
********************************************/
proc calis cov data=power method = ml nobs = 932;
lineqs
V1 = F1 + E1,
V2 = .833 F1 + E2,
V3 = F2 + E3,
V4 = .833 F2 + E4,
V5 = F3 + E5,
V6 = a6 F3 + E6,
F1 = c1 F3 + D1,
F2 = c2 F1 + c3 F3 + D2;
std
D1 - D2 = ed:,
F3 = ef3,
E1 = ee1,
e3 = ee1,
e2 = ee2,
e4 = ee2,
e5 = ee3,
e6 = ee4;
cov
E1 E3 = theta1,
E2 E4 = theta1;
run; |
Example 5: A Second-order Factor Analysis Model on page 38
|
EQS code: manul5.eqs |
SAS code |
/TITLE
A SECOND-ORDER FACTOR ANALYSIS MODEL
(EXAMPLE IN EQS MANUAL P.38)
/SPECIFICATIONS
CAS=932; VAR=6; ME=GLS;
/LABEL
V1=ANOMIA67; V2=POWRLS67;
V3=ANOMIA71; V4=POWRLS71;
V5=EDUCATON; V6=OCCUPATN;
/EQUATIONS
V1 = F1 + E1;
V2 = 2*F1 + E2;
V3 = F2 + E3;
V4 = 2*F2 + E4;
F1 = 1*F3 + D1;
F2 = 1*F3 + D2;
/VARIANCES
F3 = 1;
F3 = 1;
D1 TO D2 = 1*;
E1 TO E4 = 3*;
/CONSTRAINTS
(F1,F3) = (F2,F3);
/MATRIX
11.834
6.947 9.364
6.819 5.091 12.532
4.783 5.028 7.495 9.986
-3.839 -3.889 -3.841 -3.625 9.610
-2.189 -1.883 -2.175 -1.878 3.552 4.503
/END |
/********************************************* This example uses the same covariance matrix as in example 1. ********************************************/ proc calis cov data=power method = gls nobs=932; lineqs V1 = F1 + E1, V2 = c1 F1 + E2, V3 = F2 + E3, V4 = c2 F2 + E4, F1 = c3 F3 + D1, F2 = c3 F3 + D2; std F3 = 1, D1 - D2 = ed:, E1 - E4 = ee:; run; |
Example 6: A Nonstandard Model on page 104
|
EQS code: manul6.eqs |
SAS code |
/TITLE EXAMPLE IN EQS MANUAL P.104 /SPECIFICATIONS CASES = 122; VARIABLES = 8; MATRIX=CORRELATION; ANALYSIS=COVARIANCE; /LABELS V1 = PERFORM; V2 = SATISFC1; V3 = SATISFC2; V4 = ACHMOTV1; V5 = ACHMOTV2; V6 = SLFESTM1; V7 = SLFESTM2; V8 = VERBALIQ; F1 = JOBSATSF; F2 = N-ACHIEV; F3 = ESTEEM; /EQUATIONS V1 = 1*F3 + .5*V8 + E1; V2 = F1 + E2; V3 = 1*F1 + E3; V4 = F2 + E4; V5 = 1*F2 + E5; V6 = F3 + E6; V7 = 1*F3 + E7; F1 = 1*F2 + .5*V1 + D1; /VARIANCES V8 = 10*; F2 TO F3 = 1*; E1 TO E7 = 5*; D1 = 1*; /COVARIANCES F2,F3 = *; F2,V8 = *; F3,V8 = *; /MATRIX 1.000 .418 1.000 .394 .627 1.000 .129 .202 .266 1.000 .189 .284 .208 .365 1.000 .544 .281 .324 .201 .161 1.000 .507 .225 .314 .172 .174 .546 1.000 -.357 -.156 -.038 -.199 -.277 -.294 -.174 1.000 /STANDARD DEVIATIONS 2.09 3.43 2.81 1.95 2.08 2.16 2.06 3.65 /print effect=yes; covariance=yes; correlation=yes; /LMTEST /wtest /END |
data bagozzi (TYPE=CORR);
input _type_ $ _name_ $ v1-v8;
label V1 = 'PERFORM'
V2 = 'SATISFC1'
V3 = 'SATISFC2'
V4 = 'ACHMOTV1'
V5 = 'ACHMOTV2'
V6 = 'SLFESTM1'
V7 = 'SLFESTM2'
V8 = 'VERBALIQ';
datalines;
mean . 0 0 0 0 0 0 0 0
std . 2.09 3.43 2.81 1.95 2.08 2.16 2.06 3.65
N . 122 122 122 122 122 122 122 122
corr v1 1.000 . . . . . . .
corr v2 .418 1.000 . . . . . .
corr v3 .394 .627 1.000 . . . . .
corr v4 .129 .202 .266 1.000 . . . .
corr v5 .189 .284 .208 .365 1.000 . . .
corr v6 .544 .281 .324 .201 .161 1.000 . .
corr v7 .507 .225 .314 .172 .174 .546 1.000 .
corr v8 -.357 -.156 -.038 -.199 -.277 -.294 -.174 1.000
;
run;
proc calis cov data = bagozzi pall;
lineqs
V1 = a1 F3 + a2 V8 + E1,
V2 = F1 + E2,
V3 = c1 F1 + E3,
V4 = F2 + E4,
V5 = d1 F2 + E5,
V6 = F3 + E6,
V7 = e1 F3 + E7,
F1 = f1 F2 + f2 V1 + D1;
std
V8 = ev8,
F2 - F3 = ef2 - ef3,
E1 - E7 = ee1 - ee7,
D1 = ed1;
cov
F2 F3 = theta1,
F2 V8 = theta2,
F3 V8 = theta3;
run; |
Example 7: A Simulated Confirmatory Factory Analysis Example on page 117
|
EQS code: manul7.eqs |
SAS code |
/TITLE
SIMULATED CONFIRMATORY FACTOR ANALYSIS EXAMPLE
(EXAMPLE IN EQS MANUAL P.117)
RAW SCORES IN BENTLER (1985, P.105)
DEFAULT START VALUES
/SPECIFICATIONS
CASES = 50; VARIABLES = 6; ME = ML, ROBUST;
MA = RA; FO='(1X,6F6.3)'; DATA='MANUL7.DAT';
/EQUATIONS
V1 = *F1 + E1;
V2 = *F1 + E2;
V3 = *F1 + E3;
V4 = *F2 + E4;
V5 = *F2 + E5;
V6 = *F2 + E6;
/VARIANCES
F1 TO F2 = 1;
E1 TO E6 = *;
/COVARIANCE
F1,F2 = *;
/diagram
title='Diagram from Manul7'; tlocation=top;
oritntation=landscaape; border=yes;
postscript='MANUL7.PS';
layout = e1 v1 b b b b b v4 e4&
e2 v2 b f1 b f2 b v5 e5&
e3 v3 b b b b b v6 e6;
/END |
data data67; proc calis cov data = data67 method = ml; lineqs V1 = a1 F1 + E1, V2 = b1 F1 + E2, V3 = c1 F1 + E3, V4 = d1 F2 + E4, V5 = e1 F2 + E5, V6 = f1 F2 + E6; std F1 = 1, F2 = 1, E1 - E6 = ee:; cov F1 F2 = theta1; run; |
Example 8: Growth in Wisc Scores on page 175
|
EQS code: manul9.eqs |
SAS code |
/TITLE
GROWTH IN WISC SCORES
(EXAMPLE IN EQS MANUAL P. 175)
OSBORNE DATA (MCARDLE & EPSTEIN, 1987, P.113)
/SPECIFICATIONS
CASES = 204; VAR = 4;
ANALYSIS=MOMENT; MATRIX = CORRELATIONS;
/EQUATIONS
V1 = F1 + E1 - 3*V999;
V2 = 1*F1 + E2;
V3 = F2 + E3;
V4 = 1*F2 + E4;
F1 = 21*V999 + D1;
F2 = 1*F1 + 8*V999 + D2;
/VARIANCES
D1 = 30*; D2 = 3*;
E1 TO E3 = 8*; E4 = 16*;
/TECHNICAL
TOL=0.01;
/PRINT
EFFECT = YES;
/MEANS
18.034 25.819 35.255 46.593
/STANDARD DEVIATIONS
6.374 7.319 7.796 10.386
/MATRIX
1.000
.809 1.000
.806 .850 1.000
.765 .831 .867 1.000
/END |
data growth (TYPE=CORR); input _type_ $ _name_ $ v1-v4; datalines; mean . 18.034 25.819 35.255 46.593 std . 6.374 7.319 7.796 10.386 N . 204 204 204 204 corr v1 1.000 . . . corr v2 .809 1.000 . . corr v3 .806 .850 1.000 . corr v4 .765 .831 .867 1.000 ; run; /**************************************************** The output of the following procedure gives the same parameter estimates and standard errors as the EQS code on the left. It is worth noticing that it uses the uncorrected standard deviation instead of corrected standard deviation for the mean as in EQS. This is because the extra constant term involved. *****************************************************/ proc calis ucov data = growth augment nobs = 204; lineqs V1 = a0 Intercept + F1 + E1, V2 = b1 F1 + E2, V3 = F2 + E3, V4 = b4 F2 + E4, F1 = d0 Intercept + D1, F2 = e0 Intercept + e1 F1 + D2; std d1 = ed1, d2 = ed2, E1 -E4 = ee:; run; |
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