View source: R/computeCriteria.R
computeCriteria | R Documentation |
A function that returns a named vector of evaluated criteria for each respective item in the test bank. The names are associated with the item number in the bank. Note that criteria values are returned such that the maximum value always represents the most optimal item (e.g., maximum information). In cases where the minimum value is typically selected (e.g., minimum variance) all values are multiplied by -1 to turn it into a maximization problem.
computeCriteria(
x,
criteria,
person = NULL,
test = NULL,
design = NULL,
subset = NULL,
info_mats = FALSE
)
x |
an object of class 'mirtCAT_design' returned from the |
criteria |
item selection criteria (see |
person |
(required when |
test |
(required when |
design |
(required when |
subset |
an integer vector indicating which items should be included in the optimal search;
the default |
info_mats |
logical; if more than one trait is present in the test, should the respective information matricies be returned instead of the scalar summary statistics (e.g., D-rule). When TRUE will return a list of matricies associated with each respective item |
a vector of criteria values for each respective item
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v048.i06")}
Chalmers, R. P. (2016). Generating Adaptive and Non-Adaptive Test Interfaces for Multidimensional Item Response Theory Applications. Journal of Statistical Software, 71(5), 1-39. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v071.i05")}
mirtCAT
, updateDesign
, extract.mirtCAT
,
findNextItem
## Not run:
# test defined in mirtCAT help file, first example
CATdesign <- mirtCAT(df, mod, design_elements = TRUE)
computeCriteria(CATdesign, criteria = 'MI')
computeCriteria(CATdesign, criteria = 'MEI')
## End(Not run)
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