classify: Classification Accuracy and Consistency under IRT models.

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IRT classification uses the probability that candidates of a given ability, will answer correctly questions of a specified difficulty to calculate the probability of their achieving every possible score in a test. Due to the IRT assumption of conditional independence (that is every answer given is assumed to depend only on the latent trait being measured) the probability of candidates achieving these potential scores can be expressed by multiplication of probabilities for item responses for a given ability. Once the true score and the probabilities of achieving all other scores have been determined for a candidate the probability of their score lying in the same category as that of their true score (classification accuracy), or the probability of consistent classification in a category over administrations (classification consistency), can be calculated.

Author
Dr Chris Wheadon and Dr Ian Stockford
Date of publication
2014-08-17 12:17:00
Maintainer
Dr Chris Wheadon <chris.wheadon@gmail.com>
License
GPL (>= 2)
Version
1.3

View on CRAN

Man pages

across.reps-methods
Summarises classification values across bugs or jags...
beta.list
Extract Beta Values from Bugs Sims File
biology
Polytomous Responses from 200 Candidates to 31 Questions
classification-class
Class '"classification"'
classify
Calculate Classification Statistics
classify.bug
Classification Accuracy and Consistency from Bugs Replicate...
classify-package
Classification Accuracy and Consistency under IRT models.
expected.rc
Expected scores under the PCM or the GPCM.
gpcm
Generalised Partial Credit Model Derived Probabilities
gpcm.bug
Extract IRT Model Parameters from Bugs Models
gpcm.rc
IRT Derived Predicted Conditional Number Correct Score...
pcm
Partial Credit Model Derived Probabilities
physics
Dichotomous Responses from 200 Candidates to 25 Questions
plot-methods
Plot Methods for Classification and Scores s4 objects
rasch
Rasch Derived Probabilities
scores-class
Class '"scores"'
scores.gpcm.bug
Expected and Conditional Summed Score Distributions
summary-methods
Summary Statistics for S4 Class Classification
thpl
Three Parameter IRT Model Derived Probabilities
tpl
Two Parameter IRT Model Derived Probabilities
w_lord
Lord and Wingersky Recursion Formula

Files in this package

classify
classify/inst
classify/inst/CITATION
classify/inst/bugs
classify/inst/bugs/rasch.bug
classify/inst/bugs/gpcm.bug
classify/inst/bugs/tpl.bug
classify/inst/bugs/pcm.bug
classify/src
classify/src/Makevars
classify/src/exp.cpp
classify/src/rcpp_w_lord.h
classify/src/rcpp_w_lord.cpp
classify/src/Makevars.win
classify/src/gpcm.cpp
classify/src/gpcm.h
classify/src/exp.h
classify/NAMESPACE
classify/data
classify/data/biology.rda
classify/data/datalist
classify/data/physics.rda
classify/R
classify/R/bugs.R
classify/R/w_lord.R
classify/R/scores.R
classify/R/prob_functions.R
classify/R/classify.R
classify/R/gpcm.rc.R
classify/MD5
classify/DESCRIPTION
classify/man
classify/man/gpcm.bug.Rd
classify/man/rasch.Rd
classify/man/gpcm.Rd
classify/man/summary-methods.Rd
classify/man/thpl.Rd
classify/man/w_lord.Rd
classify/man/plot-methods.Rd
classify/man/classify-package.Rd
classify/man/physics.Rd
classify/man/scores-class.Rd
classify/man/gpcm.rc.Rd
classify/man/classify.Rd
classify/man/across.reps-methods.Rd
classify/man/classify.bug.Rd
classify/man/scores.gpcm.bug.Rd
classify/man/classification-class.Rd
classify/man/pcm.Rd
classify/man/biology.Rd
classify/man/expected.rc.Rd
classify/man/beta.list.Rd
classify/man/tpl.Rd