Function to simulate data from DPSD model with positive d'
dpsdPosSim(NN = 1, NS = 2, I = 30, J = 200, K = 6, muN = -0.7,
s2aN = 0.2, s2bN = 0.2, muD = c(0, 0.5), s2aD = 0.2,
s2bD = 0.2, muR = qnorm(c(0.2, 0.4)), s2aR = 0.2, s2bR
= 0.2, crit = matrix(rep(c(-1.6, -0.5, 0, 0.5, 1.6),
each = I), ncol = (K - 1)))
Number of new-item conditions.
Number of studied-item conditions.
Number of participants.
Number of items.
Number of response options.
Mean of new-item distribution. If there are more than one new-item conditions this is a vector of means with length equal to NN.
Variance of participant effects on mean of new-item distribution.
Variance of item effects on mean of new-item distribution.
Mean of dprime distribution. If there are more than new-item conditions this is a vector of means with length equal to NNone studied-item conditions this is a vector of means with length equal to NS.
Variance of participant effects on mean of dprime distribution.
Variance of item effects on mean of dprime distribution.
Mean recollection, on probit space.
Variance of participant effects recollection.
Variance of item effects on recollection.
Matrix of criteria (not including -Inf or Inf). Columns correspond to criteria, rows correspond to participants.