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irt (version 0.2.9)

Item Response Theory and Computerized Adaptive Testing Functions

Description

A collection of Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) functions that are used in psychometrics.

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Install

install.packages('irt')

Monthly Downloads

311

Version

0.2.9

License

AGPL (>= 3)

Issues

2

Pull Requests

1

Stars

2

Forks

2

Maintainer

Emre Gonulates

Last Published

February 20th, 2024

Functions in irt (0.2.9)

add_misc

Add or change a named value to 'misc' slot of an Item-class, Itempool-class or Testlet-class object.
as.data.frame.cat_output

Convert a cat_output object into a data.frame.
Testlet-class

An S4 class to represent a Testlet
as.Itempool

Coerce a given object to Itempool-class object
Response_set-class

An S4 class representing responses of a set of examinees
as.list.Itempool

This function converts Itempool objects to a list object
as.data.frame.Response

Convert a Response-class object into a data.frame.
as.data.frame.Item

Convert an Item-class object into a data.frame.
as.data.frame.Response_set

Convert a Response_set-class object into a long format data.frame
$,Item-method

Get slots from an Item-class object.
biserial

Calculate biserial correlation
area_between_icc

Calculate the area between two ICC curves
$.cat_output

Prints the raw output of cat_sim
calculate_overlap_rates

Calculate overlap rate of items for CAT
as.list.Response_set

This function converts Response_set objects to a list object
as.matrix,Response_set-method

Convert a Response_set-class object into a matrix
c,Item-method

Concatenate Item, Itempool or Testlet objects and return an Itempool object.
calculate_exposure_rates

Calculate exposure rate of items for CAT
c.cat_design

Concatenate 'cat_design' objects
$<-,Item-method

Set values to parameters or components of Item-class object
$,Testlet-method

Access slots of a Testlet-class object
$,Itempool-method

Get slots of the an Itempool-class object.
cat_sim

Computerized Adaptive Test (CAT) Simulation
cat_sim_fast

Computerized Adaptive Test (CAT) Simulation (Parallel Computing)
$,Response_set-method

Get slots of the a Response_set-class object.
$,Response-method

Get slots of the an Response-class object.
$<-,Response-method

Set values to components of 'Response' class objects
$<-,Itempool-method

Set values to parameters or components of 'Itempool' class.
$<-,Response_set-method

Set values to components of 'Response_set' class objects
$<-,Testlet-method

Set values to parameters or components of Testlet-class object
dif

Evaluate Differential Item Functioning (DIF) of a test
convert_model

Convert model parameters from one model to another
classification_agreement_index

Calculate agreement index
create_cat_design

Computerized Adaptive Test (CAT) Simulation Design
cusum_single

CUSUM based statistics for one examinee
classification_indices

Calculate classification accuracy and consistency
est_ability

Estimate Examinee Ability
distractor_analysis

Distractor Analysis Function
equate_stuirt

IRT Scale Transformation using STUIRT Program
.print.Testlet

Print a Testlet-class object
generate_resp

Generate random item responses (Response object)
est_bilog

Item Calibration via BILOG-MG
est_irtpro

Item Calibration via IRTPRO
get_cat_administered_items

Get administered items from a CAT output
generate_ip

Generate a random Itempool object
est_winsteps

Estimate Rasch Model using Winsteps
generate_testlet

Generate a random Testlet object
est_flexmirt

Unidimensional Item Calibration via flexMIRT
generate_resp_set

Generate a random item responses (Response_set object)
generate_item

Generate a random Item object
irt-package

irt: Item Response Theory and Computerized Adaptive Testing Functions
get_max_possible_total_score

Calculate the maximum score of a set of items
info

Calculates the information of an "Item" object
get_cat_response_data

Extracts the response data of CAT output.
4PL-class

Three-Parameter Logistic IRT model
is.Item

Check whether an object is an Item-class
ipd

Item Parameter Drift
1PL-class

One-Parameter Logistic IRT model
item

Create an Item object
ks

Item Characteristic Curve Estimation using Kernel Smoothing
2PL-class

Two-Parameter Logistic IRT model
3PL-class

Three-Parameter Logistic IRT model
kappa_coef

Calculate Cohen's Kappa Coefficient
item_analysis

Item Analysis Function
itempool

Create an Itempool object
item_fit

Calculate item-fit indices
length,Itempool-method

Find the length of an Itempool-class object
max_score

Calculate the maximum possible score
mean,Itempool-method

Calculate the expected value of an Itempool
mean,Item-method

Calculate the expected value of an Item
plot.Itempool

Plot Item Characteristic Curves or Test Characteristic Curve of an Itempool object
plot.Item

Plot Item Characteristic Curve of an Item object
plot_distractor_icc

Plot Empirical Item or Test characteristic curve
mean,Testlet-method

Calculate the expected value of an Testlet
print,Item-method

Print an Item-class object
person_fit

Calculate person-fit indices
plot_empirical_icc

Plot Empirical Item characteristic curve
print,Response_set-method

Print a Response_set-class object
print.bilog_output

Prints bilog_output objects
print,Response-method

Show an Response-class object
print.cat_design

Prints cat_design objects.
print,Itempool-method

Show an Itempool-class object
prob

Calculate the probability of a correct response
plot.ks_output

Plot Item Fit using Kernel-Smoothing
plot_resp_loglik

Plot the Log-Likelihood of a response string
prob_sum_score

Calculate summed-score probabilities
plot_empirical_icc2

Plot Empirical Item Characteristic Curve
plot_info

Plot Item Information Function
plot.cat_output

Plot progress of a CAT algorithm for one examinee
print.cat_output

This method prints an "cat_output" class object
resp_lik

Likelihood of a response string
rsss

Convert raw score to scale score and vice versa
score_info

Calculate Score Information Function
response

Create a Response object from a vector of responses
point_biserial

Calculate point-biserial correlation
rmsd

Calculate Root Mean Square Deviation (RMSD) (or Root Mean Square Error (RMSE))
qip_index

Calculate Quality of Item Pool Index
score_raw_resp

Score Raw Responses
[[<-,Response_set,numeric,missing-method

Set the elements of an Response_set objects.
[,Testlet,ANY,missing-method

Subset Testlet-class object
[[<-,Itempool,numeric,missing-method

Set the elements of an Itempool objects.
show.cat_output

This method shows an "cat_output" class object
response_set

Create Response_set-class object
show,Item-method

Show an Item-class object
var,Testlet-method

Calculate the variances of items in a Testlet
sim_resp

Generate responses for a given model
var,Itempool-method

Calculate the variances of items in an Itempool
resp_loglik

Log-likelihood of a Response String
[,Itempool,ANY,missing-method

Subset Itempool objects
[[,Response_set,numeric,missing-method

Subset Response_set objects
[[,Testlet,numeric,missing-method

Access the items of a Testlet-class object.
summary.cat_output

Summarizes the raw output of cat_sim
var,Item-method

Calculate the variance of an Item
testlet

Creates a Testlet-class object
[[,Itempool,numeric,missing-method

Subset Itempool objects
[,Response_set,ANY,missing-method

Subset Response_set objects
[[<-,Testlet,numeric,missing-method

This function sets the elements of a Testlet objects.
summary.list

If a list object consists of all "cat_output" objects, then it will run summary.cat_output.
Rasch-class

Rasch model
M2PL-class

Multidimensional Two-Parameter Logistic Model
Itempool-class

An S4 class to represent an Itempool
M3PL-class

Multidimensional Three-Parameter Logistic Model
GPCM-class

Generalized Partial Credit Model
Response-class

An S4 class representing responses of a single examinee
Item-class

An S4 class to represent an Item
GPCM2-class

Reparameterized Generalized Partial Credit Model
GRM-class

Graded Response Model
PCM-class

Partial Credit Model