lazy.irt {lazy.irt} R Documentation

lazy.irt: Some IRT functions for lazy boys and girls

Description

The following are the classes of the functions.

Parameter Estimation and Equating

• uIRT: Item Parameter Estimation of Unidimensional IRT

• 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

est_theta: Estimation of Theta

• ordinal_reg: Oridinal Regression (used in the m-step of uIRT)

Item Response Functions

• 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 (N.A.)

• 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

Derivative of Item Response Functions

• dirf: Calculation of Derivative of Item Response Function

• dicrfB: Calculation of the Derivative of Item Response Function of Binary Logistic Items

• dicrfG: Calculation of the Derivative of Item Response Function of Graded Response Items

• dicrfN: Calculation of the Derivative of Item Response Function of Nominal Items (N.A.)

• dicrfP: Calculation of the Derivative of Item Response Function of Partial Credit Items

• dicrfPN: Calculation of the Derivative of Item Response Function of Partial Credit Items in Nominal Format

• dicrfPN0: Calculation of the Derivative of Partial Credit ICRF in Nominal format

• dicrf_num: Numerical Derivative of Item Response Function using JacobianMat

• dirf_p: Calculation of the Derivative of Item Response Function with respect to Item Parameters

Observed Score Distributions

• 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

• rel_irt: Calculation of Test Reliability and Average SEM under IRT model

Information Functions

• info_func: Calculation of Various Information Functions

• graded_info: Calculation of the Information Function associated with the Graded Observed Score.

• flatten_SEM: Find the Transformation of the Observed Score such that the Resulting Score has a Flat SEM almost everywhere.

• flatten_SEM_theta: Find the Transformation of the Thetahat Based Observed Score such that the Resulting Score has a Flat SEM almost everywhere.

Conversion Functions

• fitG2P: Approximate Conversion of Partial Credit Items to Graded Response Items Using Logit Transformation

• fitP2G: Approximate Conversion of Graded Response Items to Partial Credit Items Using Logit Transformation

• fitG2P_ls: Conversion of Partial Credit Items to Graded Response Items

• fitP2G_ls: Conversion of Graded Response Items to Partial Credit Items

• fit223_ls: Conversion of 3PLM Items to 2PLM Items

• 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

Utility Functions

• checkparam: Checking Parameter Data Frame

• gendataIRT: Generation of Simulated Item Response Data

• find_mode: Find the Mode of icrf

• find_intersection: Find the Intersection of icrfs

• gen_icrfnames: Generate the row names of vec(icrf)

Data

• paramA1: Set of All Types of Items # 1. (10 items)

• paramB1: Binary Item Parameter Data Frame # 1. (18 2PLM items)

• paramB2: Binary Item Parameter Data Frame # 2. (18 3PLM items)

• paramS1: Small Item Parameter Data Frame # 1. (3 mixed type items)

• paramS2: Small Item Parameter Data Frame # 2. (8 mixed type items)

• paramS3: Small Item Parameter Data Frame # 2. (20 mixed type 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.

LRT

• uLRT: Item Parameter Estimation of Unidimensional LRT
with strict monotonicity restrictions.

• est_rank: Estmation of LRT latent rank for each person.

• fitI2L: Approxiamte Conversion of LRT model to 2PLM IRT model

• fitI2L_ls: LS Conversion of LRT model to 2PLM IRT model

[Package lazy.irt version 0.1.3 Index]