| fitG2P {lazy.irtx} | R Documentation |
Approximate Conversion of Partial Credit Items to Graded Response Items Using Logit Transformation
fitG2P(paramP, wtype = 1, DinP = 1, dataframe = 1, npoints = 21, thmin = -3, thmax = 3, maxabsv = 1, print = 1, plot = 0, debug = 0)
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 |
Graded Response Model Item Parameter Data Frame
paramG1 <- fitG2P( paramS1[4,], npoints=21, plot=1, print=1 )