Simulation of data using a previous analysis requires only an ICC vector and two objects computed by function theta.distn along with a specification of the number of simulated the simulated persons.
SimulateData(nsim, indfine, denscdf, SfdList)An nsim by n matrix of integers including 1 and 2 that specify each person's option choice for each item.
Number of persons having simulated choices.
The score index values within [0,100] that are
associated with the cumulative probability values in
denscdf.
The cumulative probability values within [0,1]. The values have to be discrete, begin with 0 and end with 1.
List vector of length n of list vectors for item objects.
Juan Li and James Ramsay
Arguments indfine and denscdf can be obtained from
the original analysis, but also can be specified to describe
a different distribution of score index values.
Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.
Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.
dataSimulation,
chcemat_simulate