Factorial research designs are experiments involving factorial combinations of independent variables. Factor combinations involve pairing each level of an independent variable with each level of a second independent variable. Factor combinations allow you to determine the effect of each independent variable individually (main effect) and the effect of the independent variables in combination (interaction effect). The simplest possible experiment involves a two-level manipulated independent variable. Likewise, the simplest possible factorial design involves two independent variables, each with two levels. Factorial designs are identified by specifying the number of levels of each of the independent variables in the experiment. A 2 x 2 design, therefore, identifies the most basic factorial design in research. Regardless of the number of independent variables, the number of conditions in a factorial design can be determined by multiplying the number of levels of the independent variables. Factorial designs can also be extended beyond the 2 x 2 design in two ways. Experimenters can add levels such as 3 x 2, 3 x 3, 4 x 2, 4 x 3, and so on. Experimenters can also build on the 2 x 2 design by increasing the number of independent variables in the same experiment. The number of levels of each variable can range from 2 to an unspecified upper limit. Adding a third or fourth independent variable produces designs such as 2 x 2 x 2, 3 x 3 x 3, 2 x 2 x 4, 2 x 3 x 3 x 2, and so on (CITE). Kaiser, Vick, and Major (2006) conducted a factorial experiment using the emotional Stroop task to investigate whether women with the expectation of being stigmatized due to sexism would demonize… half of paper… word type variable. The main effect of word type was statistically significant. Kaiser et al. I found that, overall; women paid more attention to social identity-threatening cues than to both disease-threatening and non-threatening cues. There was no difference, however, between the latter two conditions. These results indicated that, when they were aware of the types of words, women paid more attention to words that indicated a threat to their social identity. Kaiser et al. also tested for the main effect of the social identity variable by averaging the word type variable, the means for the identity threat condition, and the identity security condition. Kaiser et al. found that the main effect of the social identity variable was not statistically significant, indicating that response times were similar for women in the threat and safety conditions.