to discriminate targets from lures based on recollection alone) would equal for the d'R case in which = (and would be represented by if the variances are da-R σR0 σR1 unequal). For this simulation, the means of the familiarity and recollection lure distributions (µF0 and µR0, respectively) were both set to 0, and their corresponding standard deviations (σF0 and respectively) were both set to 1. The means of the familiarity σR0, and recollection target distributions (µF1 and µR1, respectively) were set to 0.80 and 1.0, respectively, and their corresponding standard deviations (σF1 and respectively) σR1, were set to 1.0 and 1.4, respectively. Thus, an equal-variance model was assumed to underlie the familiarity process. This matches an assumption made by the DPSD model proposed by Yonelinas (1994), but it is not a necessary assumption of the CDP model. On the recollection dimension, the Remember criterion was placed 1.8 standard deviations above the mean of the recollection lure distribution (µR0). On the familiarity dimension, the Know criterion was placed 1.5 standard deviations above the mean of the familiarity lure distribution (µF0). For Old/New decisions, values drawn from the recollection and familiarity dimensions were summed. Thus, the mean of the target and lure distributions upon which old new decisions are based are given by: µTarget = µF1 + µR1 , = µF0 + µR0 , and the corresponding variances are given by: = + + 2ρ1·σF1·σR1 , σ2Target σ2F1 σ2R1 = + + 2ρ0·σF0·σR0 σ2Lure σ2F0 σ2R0
to discriminate targets from lures based on recollection alone) would equal d'R for the case in which σR0 = σR1 (and would be represented by da-R if the variances are unequal). For this simulation, the means of the familiarity and recollection lure distributions (µF0 and µR0, respectively) were both set to 0, and their corresponding standard deviations (σF0 and σR0, respectively) were both set to 1. The means of the familiarity and recollection target distributions (µF1 and µR1, respectively) were set to 0.80 and 1.0, respectively, and their corresponding standard deviations (σF1 and σR1, respectively) were set to 1.0 and 1.4, respectively. Thus, an equal-variance model was assumed to underlie the familiarity process. This matches an assumption made by the DPSD model proposed by Yonelinas (1994), but it is not a necessary assumption of the CDP model. On the recollection dimension, the Remember criterion was placed 1.8 standard deviations above the mean of the recollection lure distribution (µR0). On the familiarity dimension, the Know criterion was placed 1.5 standard deviations above the mean of the familiarity lure distribution (µF0). For Old/New decisions, values drawn from the recollection and familiarity dimensions were summed. Thus, the mean of the target and lure distributions upon which old new decisions are based are given by: µTarget = µF1 + µR1 , = µF0 + µR0 , and the corresponding variances are given by: σ2Target = σ2F1 + σ2R1 + 2ρ1·σF1·σR1 , σ2Lure = σ2F0 + σ2R0 + 2ρ0·σF0·σR0