Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged idiosyncratic graph modification to clarify and enhance important data patterns. The current study sought to determine whether such modifications, made with and without a disclaimer regarding their purpose, would impact visual analysts’ decisions about the presence and magnitude of an intervention effect. A total of 444 behavior analysis graduate students viewed single-case data displayed in linear graphs and rated the magnitude of intervention effect of graphs in three conditions: Standard Assembly, Unstandardized Assembly, and Unstandardized Assembly with Disclaimer. The results of the study indicate that participants who viewed unstandardized linear graphs, with or without a disclaimer, rated intervention effects as significantly larger than those who viewed standardized graphs (F(2, 291.62) = 83.93, p < .000). Implications regarding data visualization in both applied and research contexts are presented.