default_dcm_priors: Default priors for diagnostic classification models
In wjakethompson/measr: Bayesian Psychometric Measurement Using 'Stan'
default_dcm_priors R Documentation
Default priors for diagnostic classification models
Description
Default priors for diagnostic classification models
Usage
default_dcm_priors(type = "lcdm", attribute_structure = "unconstrained")
Arguments
type
Type of DCM to estimate. Must be one of
lcdm, dina, dino, or crum.
attribute_structure
Structural model specification. Must be one of
unconstrained, or independent.
unconstrained makes no assumptions about the relationships between
attributes, whereas independent assumes that proficiency statuses on
attributes are independent of each other.
Value
A measrprior object.
Examples
default_dcm_priors(type = "lcdm")
wjakethompson/measr documentation built on April 12, 2025, 9:46 p.m.
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| default_dcm_priors | R Documentation |
Default priors for diagnostic classification models
Description
Default priors for diagnostic classification models
Usage
default_dcm_priors(type = "lcdm", attribute_structure = "unconstrained")
Arguments
type |
Type of DCM to estimate. Must be one of lcdm, dina, dino, or crum. |
attribute_structure |
Structural model specification. Must be one of
unconstrained, or independent.
|
Value
A measrprior object.
Examples
default_dcm_priors(type = "lcdm")
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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