| lazy.irt {lazy.irtx} | R Documentation |
The following are the classes of the functions.
uIRT: Item Parameter Estimation of Unidimensional IRT
ordinal_reg: Oridinal Regression
cala: Calibration of Independently Estimated Sets of Item Parameters by Minimizing the LS Criterion Defined in terms of Parameter Values
calr Calibration of Independently Estimated Sets of Item Parameters
by Minimizing the LS Criterion Defined in terms of Probability Values
esttheta: Estimation of Theta
irf Calculation of Item Response Function
icrfB: Calculation of item Response Function of Binary Logisticitems
icrfG: Calculation of item Response Function of Graded Responseitems
icrfN: Calculation of item Response Function of Nominalitems
icrfP: Calculation of item Response Function of Partial Credititems
icrfPN: Calculation of item Response Function of Partial Credititems in Nominal Model Format
icrfPN0: Calculation of Partial Credit ICRF in Nominal format
dirf: Calculation of Derivative of item Response Function
dicrfB: Calculation of the Derivative of item Response Function of Binary Logisticitems
dicrfG: Calculation of the Derivative of item Response Function of Graded Responseitems
dicrfN: Calculation of the Derivative of item Response Function of Nominalitems
dicrfP: Calculation of the Derivative of item Response Function of Partial Credititems
dicrfPN: Calculation of the Derivative of item Response Function of Partial Credititems in Nominal Format
dicrfPN0: Calculation of the Derivative of
Partial Credit ICRF in Nominal format
dirf_p: Calculation of the Derivative of item Response Function with respect to Item Parameters
obscore: Calculation of Observed Score Distribution and Posterior
Distribution of Theta with Various Information Functions
smn: Parameter Estimation of Parametric (Normal pdf) Scored Multinomial Distributions
sumsmnw: Distribution of the Weighted Sum of Several Independent Scored Multinomial Distributions
sumsmnw12: Distribution of the Weighted Sum of Two Independent Scored Multinomial Distributions
info_func: Calculation of Various Information Functions
graded_info: Calculation of the Information Function associated with the Graded Observed Score.
fitG2P: Approximate Conversion of Partial Credititems to Graded Responseitems Using Logit Transformation
fitP2G: Approximate Conversion of Graded Responseitems to
Partial Credititems Using Logit Transformation
convP2N: Convert Partial Credit Item Parameters to in Nominal Format
convP2PN: Convert Partial Credit Item Parameters in Standard Format to Partial Credit Parameters in Nominal Format
convPN2P: Convert Partial Credit Item Parameters in Nominal Format to Standard Format
read.param: Reading Parameter File
read.weight: Reading Weight File
checkparam: Checking Parameter Data Frame
gendataIRT: Generation of Simulated Item Response Data
dummy_expand: Dummmy Expantion of Categorical Data
paramS1: Small Item Parameter Data Frame # 1. (3 items)
paramS2: Small Item Parameter Data Frame # 2. (8 items)
paramS3: Small Item Parameter Data Frame # 2. (20 items)
weightS1: Small Item Weight Data Frame # 1 To be used in conjunction with paramS1.
weightS11: Small Item Weight Data Frame # 2. To be used in conjunction with paramS1.
weightS12: Small Item Weight Data Frame # 3. To be used in conjunction with paramS1.
weightS2: Small Item Weight Data Frame # 4. To be used in conjunction with paramS2.
weightS21: Small Item Weight Data Frame # 5. To be used in conjunction with paramS2.
weightS22: Small Item Weight Data Frame # 6. To be used in conjunction with paramS2.
weightS3: Small Item Weight Data Frame # 7.
To be used in conjunction with paramS3.
paramCal1: Small Item Parameter Data Frame for Testing cala and calr #1.
paramCal2: Small Item Parameter Data Frame for Testing cala and calr #2.