Documentation Example 10 for PROC CALIS
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: CALEX204 */
/* TITLE: Documentation Example 10 for PROC CALIS */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: PATH, measurement error models, multiple predictors */
/* PROCS: CALIS */
/* DATA: */
/* */
/* SUPPORT: yiyung UPDATE: November 5, 2009 */
/* REF: PROC CALIS, Example 10 */
/* MISC: */
/****************************************************************/
data pg214(type=cov);
input _type_ $ 1-4 _name_ $ 6-8 @10 y x1 x2 x3;
datalines;
mean 1.1349 1.5070 1.9214 3.5020
cov y 1.2129 1.2059 0.2465 4.3714
cov x1 1.2059 1.2706 0.1633 4.4813
cov x2 0.2465 0.1633 1.1227 0.6250
cov x3 4.3714 4.4813 0.6250 16.6909
;
/* Path Model */
title2 'Wayne Fuller''s Original Measurement Error Model: Page 214-215';
proc calis data=pg214 method=ml nobs=43;
path
Fy <=== F1 F2 F3,
F1 ===> x1 = 1.,
F2 ===> x2 = 1.,
F3 ===> x3 = 1.,
Fy ===> y = 1.;
pvar
x1-x3 y = .01 .01 .1403 .01;
pcov
x1 x3 = 0.0301;
mean
x1-x3 y = 4 * 0.,
F1-F3 Fy;
run;
/* Lineqs Model */
proc calis data=pg214 method=ml nobs=43;
lineqs
Fy = alpha * Intercept + b1 * F1 + b2 * F2 + b3 * F3 + DFy,
x1 = 0. * Intercept + 1 * F1 + e1,
x2 = 0. * Intercept + 1 * F2 + e2,
x3 = 0. * Intercept + 1 * F3 + e3,
y = 0. * Intercept + 1 * Fy + ey;
variance
e1-e3 ey = .01 .01 .1403 .01;
cov
e1 e3 = 0.0301;
mean
F1-F3;
run;
data multiple(type=cov);
input _type_ $ 1-4 _name_ $ 6-8 @10 y x1 x2 x3;
datalines;
mean 0.93 1.33 1.34 4.11
cov y 1.31 . . .
cov x1 1.24 1.42 . .
cov x2 0.21 0.18 1.15 .
cov x3 3.91 4.21 0.58 14.11
;
proc calis data=multiple nobs=37;
path
Fy <=== F1 F2 F3,
F1 ===> x1 = 1.,
F2 ===> x2 = 1.,
F3 ===> x3 = 1.,
Fy ===> y = 1.;
pvar
x1 x2 x3 y = .02 .03 .15 .02,
Fy;
run;
proc calis data=multiple nobs=37;
path
Fy <=== F1 F2 F3,
F1 ===> x1 = 1.,
F2 ===> x2 = 1.,
F3 ===> x3 = 1.,
Fy ===> y = 1.;
pvar
x1 x2 x3 y = .02 .03 .15 .02,
Fy;
pcov
x1 x2 = 0.01;
run;