gen.data {ConvertPar} | R Documentation |
Generating Dichotomous Data Sets based on Logistic IRT Models (Rasch, 2PL, 3PL).
Description
This function can be used for generating dichotomous response matrices based on Logistic IRT Models. Sample size, item number, parameter distributions can be specified.
Usage
gen.data(model="2PL",samplesize=1000,itemsize=100,
theta.mean=0,theta.sd=1, a.mean=0, a.sd=0.2,b.mean=0,
b.sd=1, c.min=0, c.max=0.25)
Arguments
model |
string: option for desired IRT model. 'Rasch', '2PL' or '3PL' ('2PL' is default) |
samplesize |
numeric: Desired Sample size (Default 1000). |
itemsize |
numeric: Desired item number (Default 100). |
theta.mean |
numeric: mean value of theta normal distribution (Default 0). |
theta.sd |
numeric: standart deviation of theta normal distribution (Default 1). |
a.mean |
numeric: mean value of a parameters log normal distribution (Default 0). |
a.sd |
numeric: standart deviation of a parameters log normal distribution (Default 0.2). |
b.mean |
numeric: mean value of b parameters normal distribution (Default 0). |
b.sd |
numeric: standart deviation of b parameters normal distribution (Default 1). |
c.min |
numeric: minimum value of c parameters uniform distribution (Default 0). |
c.max |
numeric: maximum value of c parameters uniform distribution (Default 0.25). |
Value
This function returns a a data frame
containing simulated dichotomous response matrix.
Examples
gen.data(model="2PL",
samplesize=1000,
itemsize=100,
theta.mean=0,
theta.sd=1,
a.mean=0,
a.sd=0.2,
b.mean=0,
b.sd=1,
c.min=0,
c.max=0.25)