* This is file VENTRICL.SAS ;
* Create data set from pulmonary artery constriction only ;
DATA;
infile vent1;
input Aed Ped Dr;
* set up to create centered variables by making copies ;
* of the variables to be centered ;
cPed=Ped;
cDr=Dr;
* use proc STANDARD with no STD specification to subtract means ;
* which overwrites cPed and cDr with centered values and retains ;
* other variables in unmodified form. ;
proc STANDARD mean=0;
var cPed cDr;
DATA vent1;
* Get last data set (from proc STANDARD) ;
set;
Ped2=Ped**2;
PedDr=Ped*Dr;
cPed2=cPed**2;
cPedDr=cPed*cDr;
LABEL Aed='Left Ventricle end-diastolic area'
Ped='Left Ventricle end-diastolic pressure'
Dr ='Right Ventrilce end-diastolic dimension'
Ped2='Squared end-diastolic pressure'
PedDr='Pressure by dimension interaction'
cPed='Centered end-diastolic pressure'
cPed2='Squared centered end-diastolic pressure'
cDr='Centered end-diastolic dimension'
cPedDr='Centered press. by dimension interaction';
* Create data set from sequence of pulmonary artery and ;
* vena caval constrictions and releases (Data in Table C-12B) ;
DATA temp1;
infile vent2;
input Aed Ped Dr;
cPed=Ped;
cDr=Dr;
proc STANDARD mean=0;
var cPed cDr;
DATA vent2;
set;
Ped2=Ped**2;
PedDr=Ped*Dr;
cPed2=cPed**2;
cPedDr=cPed*cDr;
LABEL Aed='Left Ventricle end-diastolic area'
Ped='Left Ventricle end-diastolic pressure'
Dr ='Right Ventricle end-diastolic dimension'
Ped2='Squared end-diastolic pressure'
PedDr='Pressure by dimension interaction'
cPed='Centered end-diastolic pressure'
cPed2='Squared centered end-diastolic pressure'
cDr='Centered end-diastolic dimension'
cPedDr='Centered press. by dimension interaction';
* Regression of raw (i.e., uncentered) data from first data set: Vent1 ;
* followed by centered data regression, including collinearity ;
* diagnostics with /VIF (for VIF) and COLLINOINT (for eigenvalues and ;
* condition indices from correlation matrix) ;
proc REG data=vent1;
model Aed = Ped Ped2 Dr PedDr/ VIF COLLINOINT;
model Aed = cPed cPed2 cDr cPedDr/ VIF COLLINOINT;
* Regression of raw (i.e., uncentered) data from second data set: Vent2 ;
* followed by centered data regression, including collinearity ;
* diagnostics with /VIF (for VIF) and COLLINOINT (for eigenvalues and ;
* condition indices from correlation matrix) ;
proc REG data=vent2;
model Aed = Ped Ped2 Dr PedDr/ VIF COLLINOINT;
model Aed = cPed cPed2 cDr cPedDr/ VIF COLLINOINT;