“…Multilevel modeling provides an appropriate alternative that does not suffer from these limitations because it incorporates and adjusts for each participant's reaction time on each individual trial using random effects of both participants and stimuli, greatly reducing Type I error rates (Judd, Westfall, & Kenny, 2012). Consequently, because the multilevel modeling approach leverages both within-and between-person variation in reaction times (Curran, Lee, Howard, Lane, & MacCallum, 2012), its use is becoming increasingly common in social psychology (e.g., Cho & Knowles, 2013;Van Bavel, Packer, Haas, & Cunningham, 2012;Zayas, Greenwald, & Osterhout, 2011) and has now been applied successfully to implicit bias data (e.g., Dunham, Baron, & Banaji, 2006;Skinner & Hudac, 2017;Van Bavel & Cunningham, 2009). In the current study the SAS PROC MIXED procedure (with Satterthwaite df) was used to implement multilevel models with random effects for both participants and IAT stimuli following the procedures outlined by Judd, Westfall, and Kenny (2012).…”