simCRSM: simulate data according to CRSM
In christinehohensinn/pcIRT: IRT Models for Polytomous and Continuous Item Responses

Description Usage Arguments Details Value Author(s) References See Also Examples

With this function data sets according to the Continous Rating Scale Model are simulated

1	simCRSM(itempar, disp, perspar, mid = 0.5, len = 1, seed = NULL)

`itempar`	a numerical vector with item parameters
`disp`	a number setting the dispersion parameter for the item set
`perspar`	a numerical vector with the person parameters
`mid`	the midpoint of the response scale (on which the data set is generated)
`len`	the length of the response scale (on which the data set is generated)
`seed`	a seed for the random number generated can optionally be set

The midpoint and the length of the response scale define the interval of the data set generated. The default of the function generates data according to a response scale between 0 and 1 - that is midpoint 0.5 and length 1.

`datmat`	simulated data set
`true_itempar`	the fixed item parameters according to the input
`true_disppar`	the fixed dispersion parameter according to the input
`true_perspar`	the fixed person parameters according to the input

Christine Hohensinn

Mueller, H. (1987). A Rasch model for continuous ratings. Psychometrika, 52, 165-181.

simMPRM

#set item parameters
item_p <- c(-1.5,-0.5,0.5,1)

#set dispersion parameter for items
dis_p <- 5

#generate person parameters by a standard normal dispersion
pp <- rnorm(50, 0,1)

#simulate data set
#this is only an illustrating example for simulating data!
#In practice, a sample size of n=50 will be too small for most application
#demands
simdatC <- simCRSM(item_p, dis_p, pp)