When the resources for experimentation are limited, experimenters usually turn to the class of 2-level fractional factorial designs. Resolution III fractional factorial designs are the smallest available designs, but they alias main effects and 2-factor interactions. The class of Resolution IV designs avoids this and provides clear estimates of the main effects, assuming that 3-factor and higher-order interactions are not active. Meanwhile, some two-factor interactions remain aliased with each other. Resolution V designs have no aliasing of main effects and two-factor interactions, assuming that all higher-order interactions are inactive. However, they are often too large for situations with six or more factors of interest. For example, with six factors, the only design capable of estimating all main effects and 2-factor interactions has 32 runs. Consequently, resource restrictions often require experimenters to use smaller designs of lower resolution, typically Resolution IV. The aliasing of effects often requires additional follow-up experimentation to de-alias all active effects. However, there are situations in which follow-up experiments are impossible to perform due to the unavailability of certain test resources. An alternative to using a 16-run Resolution IV design and a follow-up experiment is to use a design with more than 16 runs as the initial experiment. We investigated a strategy for initially augmenting a class of 16-run Resolution IV designs with either 4 or 8 runs. We use a simulation study to show that this augmentation strategy improves the ability to estimate active factors when standard analysis methods are employed. The analysis methods used in this study are Stepwise, LASSO, and Dantzig.
Alqarni et al. (Thu,) studied this question.