fitG2P {lazy.irt}R Documentation

Approximate Conversion of Partial Credit Items to Graded Response Items Using Logit Transformation

Description

Approximate Conversion of Partial Credit Items to Graded Response Items Using Logit Transformation

Usage

fitG2P(paramP, wtype = 1, DinP = 1, dataframe = 1, npoints = 21,
  thmin = -3, thmax = 3, maxabsv = 1, print = 1, plot = 0,
  debug = 0)

Arguments

paramP

Item Parameter Data Frame for Partial Credit Model

wtype

= 1 to use normal weight, else uniform

DinP

= 1 to include D=1.7 in logistic function

dataframe

= 1 to create parameter data frame, not matrix

npoints

# of discrete points for theta

thmin

Minimum value of discrete thata value

thmax

Maximum value of discrete thata value

maxabsv

Maximum absolute value of the weight

print

= 1 to print result

plot

= 1 to plot result

debug

= 1 to print intemediate result

Value

Graded Response Model Item Parameter Data Frame

Examples

paramG1 <- fitG2P( paramS1[4,], npoints=21, plot=1, print=1 )


[Package lazy.irt version 0.1.3 Index]