Learn R Programming

catR (version 1.0)

Ii: Item information functions, first and second derivatives (4PL)

Description

This command returns the item information functions for a given matrix of item parameters of the 4PL model and a given ability value. Numerical values of the first and second derivatives of the item information functions are also returned.

Usage

Ii(th, it, D=1)

Arguments

th
numeric: the ability value.
it
numeric: a matrix with one row per item and four columns, with the values of the discrimination, the difficulty, the pseudo-guessing and the inattention parameters (in this order).
D
numeric: the metric constant. Default is D=1 (for logistic metric); D=1.702 yields approximately the normal metric (Haley, 1952).

Value

  • A list with three arguments:
  • Iithe vector with item informations (one value per item)
  • dIithe vector with first derivatives of the item information functions (one value per item)
  • d2Iithe vector with second derivatives of the item information functions (one value per item)

Details

The first and second derivatives are computed algebraically from the four-parameter logistic (4PL) model (Barton and Lord, 1981). These derivatives are necessary for both the estimation of ability and the computation of related standard errors.

References

Barton, M.A., and Lord, F.M. (1981). An upper asymptote for the three-parameter logistic item-response model. Research Bulletin 81-20. Princeton, NJ: Educational Testing Service. Haley, D.C. (1952). Estimation of the dosage mortality relationship when the dose is subject to error. Technical report no 15. Palo Alto, CA: Applied Mathematics and Statistics Laboratory, Stanford University.

See Also

Pi, thetaEst

Examples

Run this code
# Loading the 'tcals' parameters 
 data(tcals)
 tcals <- as.matrix(tcals)
 
 # Response probabilities and derivatives (various th and D values)
 Ii(th=0, tcals)
 Ii(th=0, tcals, D=1.702)
 Ii(th=1, tcals)

Run the code above in your browser using DataLab