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pypsy
中文 <./README_ZH.rst>
_
DINA Model and Parameter Estimation: A Didactic <http://www.stat.cmu.edu/~brian/PIER-methods/For%202013-03-04/Readings/de%20la%20Torre-dina-est-115-30-jebs.pdf>
psychometrics package, including structural equation model, confirmatory
factor analysis, unidimensional item response theory, multidimensional
item response theory, cognitive diagnosis model, factor analysis and
adaptive testing. The package is still a doll. will be finished in
future.
unidimensional item response theory
models
- binary response data IRT (two parameters, three parameters).
- grade respone data IRT (GRM model)
Parameter estimation algorithm
------------------------------
- EM algorithm (2PL, GRM)
- MCMC algorithm (3PL)
--------------
Multidimensional item response theory (full information item factor analysis)
-----------------------------------------------------------------------------
Parameter estimation algorithm
The initial value
^^^^^^^^^^^^^^^^^
The approximate polychoric correlation is calculated, and the slope
initial value is obtained by factor analysis of the polychoric
correlation matrix.
EM algorithm
^^^^^^^^^^^^
Factor rotation
^^^^^^^^^^^^^^^
Gradient projection algorithm
The shortcomings
GH integrals can only estimate low dimensional parameters.
--------------
Cognitive diagnosis model
-------------------------
models
~~~~~~
- Dina
- ho-dina
parameter estimation algorithms
Structural equation model
Confirmatory factor analysis
-
can be used for continuous data, binary data and ordered data.
-
based on gradient descent
-
binary and ordered data based on Polychoric correlation matrix.
Factor analysis
For the time being, only for the calculation of full information item
factor analysis, it is very simple.
The algorithm
principal component analysis
The rotation algorithm
gradient projection
Adaptive test
model
Thurston IRT model (multidimensional item response theory model for
personality test)
Algorithm
Maximum information method for multidimensional item response theory
Require
How to use it
See demo in detail
TODO LIST
-
theta parameterization of CCFA
-
parameter estimation of structural equation models for multivariate
data
-
Bayesin knowledge tracing (Bayesian knowledge tracking)
-
multidimensional item response theory (full information item factor
analysis)
-
high dimensional computing algorithm (adaptive integral, etc.)
-
various item response models
-
cognitive diagnosis model
-
G-DINA model
-
Q matrix correlation algorithm
-
Factor analysis
-
maximum likelihood estimation
-
various factor rotation algorithms
-
adaptive
-
adaptive cognitive diagnosis
-
other adaption model
-
standard error and P value
-
code annotation, testing and documentation.
Reference
DINA Model and Parameter Estimation: A Didactic <http://www.stat.cmu.edu/~brian/PIER-methods/For%202013-03-04/Readings/de%20la%20Torre-dina-est-115-30-jebs.pdf>
__
Higher-order latent trait models for cognitive diagnosis <http://www.aliquote.org/pub/delatorre2004.pdf>
__
Full-Information Item Factor Analysis. <http://conservancy.umn.edu/bitstream/11299/104282/1/v12n3p261.pdf>
__
Multidimensional adaptive testing <http://media.metrik.de/uploads/incoming/pub/Literatur/1996_Multidimensional%20adaptive%20testing.pdf>
__
Derivative free gradient projection algorithms for rotation <https://cloudfront.escholarship.org/dist/prd/content/qt9938p4wc/qt9938p4wc.pdf>
__
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History
0.0.1 (2018-09-18)