A new paper accepted at Behavior Research Methods examines parameter recovery for time-variant evidence accumulation models. Evidence accumulation models have been one of the most dominant modeling frameworks used to study rapid decision-making over the past several decades. These models propose that evidence accumulates from the environment until the evidence for one alternative reaches some threshold, typically associated with caution, triggering a response. However, researchers have recently begun to reconsider the fundamental assumptions of how caution varies with time. In the past it was typically assumed that levels of caution are independent of time. Recent investigations have however suggested the possibility that levels of caution decrease over time and that this strategy provides more efficient performance under certain conditions. This paper provides the first comprehensive assessment of this newer class of models accounting for time varying caution to determine how robustly their parameters can be estimated.