Screening designs effects estimation

When such time effect is present, the design responses are corrected relative to the (nominal) experiment performed at the beginning of the experimental design (Eq. 2.10) (Figure 2.16) (5,16,106). These corrected responses are then used to estimate the factor effects from screening designs or to build the model from response surface designs (see further). From both the estimated effects and the model coefficients then the time effect has been removed ... 

All factor screening designs are intended for situations in which there are too many factors to study in detail. If the number of factors is very large and/or each experimental run is very expensive, then it may be impractical to use even the Resolution III two-level designs of Chapter 1, which allow all main effects to be estimated. In such cases, it might be useful to run experiments with fewer runs than there are factors to try to identify a small number of factors that appear to have dominant effects. 

The ability to reproduce the pilot experiment is therefore a good check to see if a screening design will be meaningful. There is another benefit of a replicated pilot experiment the observed variations in response give an estimate of the experimental error, which then can be used to evaluate the significance of estimated effects. 

Screening designs are mainly used to estimate the effects of factors in an analytical investigation on a statistical basis. To understand the test procedure, we will consider an example from kinetic - enzymatic determinations. 

In contrast to the simultaneous factorial design study, experimentation by variation of one variable at a time is limited to the estimation of main effects, and no interactions, as are common in analytical chemistry, can be found. What cannot be evaluated with screening designs are curved dependences, that is, for more complicated relationships between responses and factors, designs at three or more factor levels are needed. 

---