dirf {lazy.irt}R Documentation

Calculation of Derivative of Item Response Function

Description

Calculation of Derivative of Item Response Function

Usage

dirf(param, theta = NULL, weight = NULL, zero = 1, smallP = 1e-09,
  thmin = -4, thmax = 4, npoints = 21, DinP = 1, numderiv = 0,
  eps = 1e-06, log = 0, print = 1, debug = 0, plot = 0)

Arguments

param

Item Parameter Data Frame

theta

Discrete theta values

weight

Weight data frame

zero

= 0 to exclude the xzero-th category from output

smallP

Minimum value of probability

thmin

Minimum value of discrete thata value

thmax

Maximum value of discrete thata value

npoints

# of discrete points for theta

DinP

= 1 to include D=1.7 in logistic function

numderiv

= 1 to use numerical derivatives

eps

eps for JacobianMat

log

= 1 to calculate log derivatives

print

= 1 to print result

debug

= 1 to print intemediate result

plot

= 1 to plot result

Value

A list of
dICRF, dIRF, dTRF, fromP, toP=toP, vecv, minscore_i, maxscore_i, minscore_t, maxscore_tt, log
where
dICRF npoints x sum(ncat)
dIRF npoints x nitems weighted by item category weight
dTRF npoints x 1 weighted by item category weight
and item weight
fromP, toP location of each item category in dICRF
vectorize category weights
minscore_i mimimum score of each item
maxscore_i maximum score of each item
minscore_t mimimum score of test
maxscore_t maximum score of test
Note that when log=1, dICRF etc are the log derivatives, namely, the derivative of log ICRF w.r.t. theta, etc.

Examples

dirf( paramS1, plot=1 )

# compare analytic and numeric derivative
res1=dirf( paramS1, print=0, plot=0 )$dICRF
res2=dirf( paramS1, print=0, numderiv=1, plot=0 )$dICRF
Print(max(abs(res1-res2)))


[Package lazy.irt version 0.1.3 Index]