Delta plots (DPs) graphically compare reaction time (RT) quantiles obtained under two experimental conditions. In some research areas (e.g., Simon effects), decreasing delta plots (nDPs) have consistently been found, indicating that the experimental effect is largest at low quantiles and decreases for higher quantiles. nDPs are unusual and intriguing: They imply that RT in the faster condition is more variable, a pattern predicted by few standard RT models. We describe and analyze five classes of well-established latency mechanisms that are consistent with nDPs-exhaustive processing models, correlated stage models, mixture models, cascade models, and parallel channels models-and discuss the implications of our analyses for the interpretation of DPs. DPs generally do not imply any specific processing model; therefore, it is more fruitful to start from a specific quantitative model and to compare the DP it predicts with empirical data.Keywords Delta plot . RT models . Simon effect . Activation suppression model Chronometric research in cognitive psychology often seeks to infer something about the number, nature, and temporal organization of basic information-processing components by looking at how reaction time (RT) varies across two or more experimental conditions. Classic examples of this approach using mean RT are Sternberg's (1969) additive factor method in memory scanning and Treisman and Gelade's (1980) analysis of the slope of RT versus set size functions in visual search.Increasingly, researchers have augmented the study of mean RT with studies of RT distributions. First, in some experimental paradigms, it is possible to distinguish among different classes of models on the basis of their specific predictions concerning between-condition effects on RT distributions as well as means, allowing model classes to be tested via distributional comparisons (e.g