The authors argue that implicit measures of social cognition do not reflect only automatic processes but rather the joint contributions of multiple, qualitatively different processes. The quadruple process model proposed and tested in the present article quantitatively disentangles the influences of 4 distinct processes on implicit task performance: the likelihood that automatic bias is activated by a stimulus; that a correct response can be determined; that automatic bias is overcome; and that, in the absence of other information, a guessing bias drives responses. The stochastic and construct validity of the model is confirmed in 5 studies. The model is shown to provide a more nuanced and detailed understanding of the interplay of multiple processes in implicit task performance, including implicit measures of attitudes, prejudice, and stereotyping.

The authors argue that implicit measures of social cognition do not reflect only automatic processes but rather the joint contributions of multiple, qualitatively different processes. The quadruple process model proposed and tested in the present article quantitatively disentangles the influences of 4 distinct processes on implicit task performance: the likelihood that automatic bias is activated by a stimulus; that a correct response can be determined; that automatic bias is overcome; and that, in the absence of other information, a guessing bias drives responses. The stochastic and construct validity of the model is confirmed in 5 studies. The model is shown to provide a more nuanced and detailed understanding of the interplay of multiple processes in implicit task performance, including implicit measures of attitudes, prejudice, and stereotyping.

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Social psychologists have studied the psychological processes involved in persuasion, conformity, and other forms of social influence, but they have rarely modeled the ways influence processes play out when multiple sources and multiple targets of influence interact over time. However, workers in other fields from sociology and economics to cognitive science and physics have recognized the importance of social influence and have developed models of influence flow in populations and groups-generally without relying on detailed social psychological findings. This article reviews models of social influence from a number of fields, categorizing them using four conceptual dimensions to delineate the universe of possible models. The goal is to encourage interdisciplinary collaborations to build models that incorporate the detailed, microlevel understanding of influence processes derived from focused laboratory studies but contextualized in ways that recognize how multidirectional, dynamic influences are situated in people's social networks and relationships.

Stereotype formation may be based on the exaggeration of real group differences (category accentuation) or the misperception of group differences that do not exist (illusory correlation). This research sought to account for both phenomena with J. K. Kruschke's (1996Kruschke's ( , 2001Kruschke's ( , 2003 attention theory of category learning. According to the model, the features of majority groups are learned earlier than the features of minority groups. In turn, the features that become associated with a minority are those that most distinguish it from the majority. This second process is driven by an attention-shifting mechanism that directs attention toward group-attribute pairings that facilitate differentiation of the two groups and may lead to the formation of stronger minority stereotypes. Five experiments supported this model as a common account for category accentuation and distinctiveness-based illusory correlation. Implications for the natures of stereotype formation, illusory correlation, and impression formation are discussed.