The RSREG Procedure

Example 101.1 A Saddle Surface Response Using Ridge Analysis

(View the complete code for this example.)

Myers (1976) analyzes an experiment reported by Frankel (1961) aimed at maximizing the yield of mercaptobenzothiazole (MBT) by varying processing time and temperature. Myers (1976) uses a two-factor model in which the estimated surface does not have a unique optimum. A ridge analysis is used to determine the region in which the optimum lies. The objective is to find the settings of time and temperature in the processing of a chemical that maximize the yield. The following statements produce Output 101.1.1 through Output 101.1.5:

data d;
   input Time Temp MBT;
   label Time = "Reaction Time (Hours)"
         Temp = "Temperature (Degrees Centigrade)"
         MBT  = "Percent Yield Mercaptobenzothiazole";
   datalines;
 4.0   250   83.8
20.0   250   81.7
12.0   250   82.4
12.0   250   82.9
12.0   220   84.7
12.0   280   57.9
12.0   250   81.2
 6.3   229   81.3
 6.3   271   83.1
17.7   229   85.3
17.7   271   72.7
 4.0   250   82.0
;
ods graphics on;
proc rsreg data=d plots=(ridge surface);
   model MBT=Time Temp / lackfit;
   ridge max;
run;
ods graphics off;

Output 101.1.1 displays the coding coefficients for the transformation of the independent variables to lie between –1 and 1 and some simple statistics for the response variable.

Output 101.1.1: Coding and Response Variable Information

The RSREG Procedure

Coding Coefficients for the Independent
Variables
FactorSubtracted offDivided by
Time12.0000008.000000
Temp250.00000030.000000

Response Surface for Variable MBT: Percent
Yield Mercaptobenzothiazole
Response Mean79.916667
Root MSE4.615964
R-Square0.8003
Coefficient of Variation5.7760


Output 101.1.2 shows that the lack of fit for the model is highly significant. Since the quadratic model does not fit the data very well, firm statements about the underlying process should not be based only on the current analysis. Note from the analysis of variance for the model that the test for the time factor is not significant. If further experimentation is undertaken, it might be best to fix Time at a moderate to high value and to concentrate on the effect of temperature. In the actual experiment discussed here, extra runs were made that confirmed the results of the following analysis.

Output 101.1.2: Analyses of Variance

RegressionDFType I Sum of SquaresR-SquareF ValuePr > F
Linear2313.5858030.48997.360.0243
Quadratic2146.7681440.22933.440.1009
Crossproduct151.8400000.08102.430.1698
Total Model5512.1939470.80034.810.0410

ResidualDFSum of SquaresMean SquareF ValuePr > F
Lack of Fit3124.69605341.56535139.630.0065
Pure Error33.1466671.048889  
Total Error6127.84272021.307120  

ParameterDFEstimateStandard
Error
t ValuePr > |t|Parameter Estimate
from Coded Data
Intercept1-545.867976277.145373-1.970.096482.173110
Time16.8728635.0049281.370.2188-1.014287
Temp14.9897432.1658392.300.0608-8.676768
Time*Time10.0216310.0567840.380.71641.384394
Temp*Time1-0.0300750.019281-1.560.1698-7.218045
Temp*Temp1-0.0098360.004304-2.290.0623-8.852519

FactorDFSum of SquaresMean SquareF ValuePr > FLabel
Time361.29095720.4303190.960.4704Reaction Time (Hours)
Temp3461.250925153.7503087.220.0205Temperature (Degrees Centigrade)


The canonical analysis (Output 101.1.3) indicates that the predicted response surface is shaped like a saddle. The eigenvalue of 2.5 shows that the valley orientation of the saddle is less curved than the hill orientation, with an eigenvalue of –9.99. The coefficients of the associated eigenvectors show that the valley is more aligned with Time and the hill with Temp. Because the canonical analysis resulted in a saddle point, the estimated surface does not have a unique optimum.

Output 101.1.3: Canonical Analysis

FactorCritical ValueLabel
CodedUncoded
Time-0.4417588.465935Reaction Time (Hours)
Temp-0.309976240.700718Temperature (Degrees Centigrade)
Predicted value at stationary point: 83.741940

EigenvaluesEigenvectors
TimeTemp
2.5288160.953223-0.302267
-9.9969400.3022670.953223
Stationary point is a saddle point.


However, the ridge analysis in Output 101.1.4 and the ridge plot in Output 101.1.5 indicate that maximum yields result from relatively high reaction times and low temperatures. A contour plot of the predicted response surface, shown in Output 101.1.5, confirms this conclusion.

Output 101.1.4: Ridge Analysis

Estimated Ridge of Maximum Response for Variable MBT: Percent Yield Mercaptobenzothiazole
Coded RadiusEstimated ResponseStandard
Error
Uncoded Factor Values
TimeTemp
0.082.1731102.66502312.000000250.000000
0.182.9529092.64867111.964493247.002956
0.283.5582602.60227012.142790244.023941
0.384.0370982.53329612.704153241.396084
0.484.4704542.45783613.517555239.435227
0.584.9140992.40461614.370977237.919138
0.685.3900122.41098115.212247236.624811
0.785.9067672.51661916.037822235.449230
0.886.4682772.75235516.850813234.344204
0.987.0765873.13096117.654321233.284652
1.087.7328743.64856818.450682232.256238


Output 101.1.5: Ridge and Contour Plot of Predicted Response Surface

Ridge and Contour Plot of Predicted Response Surface
External File:images/rsrx1e1.png