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 )

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