Researchers often assume a strong, linear relationship between regular- and reverse-keyed items, with responses on regular-keyed items (e.g., agree) perfectly mirroring those on reverse-keyed items (e.g., disagree). The current research challenges this received view and propounds a possible nonlinear relationship, partly due to the logical tendency of midlevel respondents to disagree with both types of items. In four examples (reported human height, job satisfaction, positive-negative affect, and self-esteem; total N = 50,544), a nonlinear model consistently explained additional item variance beyond a linear model. We further demonstrate that this relationship is moderated by item characteristics such as item extremity (job satisfaction) and item softening (self-esteem). Suboptimal modeling of the relationship may result in the apparent bidmensionality of a construct that characterizes regular- and reverse-keyed items as separate factors. User-friendly syntax for the examination of nonlinearity is provided to enhance the accessibility of the procedure.