Probing, Plotting, and Interpreting Multilevel Interaction Effects // Provides a unified workflow for probing, plotting, and assessing the robustness of cross-level interaction effects in two-level mixed-effects models fitted with 'lme4' (Bates et al., 2015) doi:10.18637/jss.v067.i01. Implements simple slopes analysis following Aiken and West (1991, ISBN:9780761907121), Johnson-Neyman intervals following Johnson and Fay (1950) doi:10.1007/BF02288864 and Bauer and Curran (2005) doi:10.1207/s15327906mbr4003_5, and grand- or group-mean centering as described in Enders and Tofighi (2007) doi:10.1037/1082-989X.12.2.121. Includes a slope variance decomposition that separates fixed-effect uncertainty from random-slope variance (tau11), a contour surface plot of predicted outcomes over the full predictor-by-moderator space, and robustness diagnostics comprising intraclass correlation coefficient shift analysis and leave-one-cluster-out (LOCO) stability checks. Designed for researchers in education, psychology, biostatistics, epidemiology, organizational science, and other fields where outcomes are clustered within higher-level units.