Screening experiments are typically used when attempting to identify a few active factors in a larger pool of potentially significant factors. In general, two-level regular factorial designs are used, but Plackett-Burman (PB) designs provide a useful alternative. Although PB designs are run-efficient, they confound the main effects with fractions of strings of two-factor interactions, making the analysis difficult. However, recent discoveries regarding the projective properties of PB designs suggest that if only a few factors are active, the original design can be reduced to a full factorial, with additional trials frequently forming attractive patterns. In this paper, we show that there is a close relationship between the partial confounding in certain PB designs and their projective properties. With the aid of examples, we demonstrate how this relationship may help experimenters better appreciate the use of PB designs.