Rasch.PCA.Bayes: Rasch Residual Principal Component Analysis
In changxiulee/BayesianRasch: Bayesian Rasch Modeling
View source: R/Rasch.PCA.Bayes.R
Description
This is for unidimensionality assumption check. If the data is unidimensional,
the eigenvalue for the first constrast should be less than 2. However, when
the eigenvalue is more than 2, it can either indicate a local change in intensity
or the multidimensionality. To know this, use the item.selection method. Rasch's parameter in this function
is estimated using Bayesian.
Usage
1
Rasch.PCA.Bayes(obj)
Arguments
obj
A BPCM or BRSM obj
changxiulee/BayesianRasch documentation built on Nov. 18, 2019, 6:54 a.m.
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View source: R/Rasch.PCA.Bayes.R
Description
This is for unidimensionality assumption check. If the data is unidimensional, the eigenvalue for the first constrast should be less than 2. However, when the eigenvalue is more than 2, it can either indicate a local change in intensity or the multidimensionality. To know this, use the item.selection method. Rasch's parameter in this function is estimated using Bayesian.
Usage
1 | Rasch.PCA.Bayes(obj)
|
Arguments
obj |
A BPCM or BRSM obj |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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