calc.info.trace: Trace of information matrix
In susanne-frick/MFCblockInfo: compute block information for multidimensional forced-choice questionnaires
View source: R/calc_info_trace.R
calc.info.trace R Documentation
Trace of information matrix
Description
calculates the traits (= sum of diagonal elements) of the information matrix
Usage
calc.info.trace(infos, avg = F, prior = NULL)
Arguments
infos
block information as returned from calc.info.block()
avg
logical, average result across persons? defaults to FALSE
prior
prior covariance matrix for the traits, defaults to NULL
Details
This is the criterion of A-optimality used in computerized adaptive testing (CAT).
It can be used to summarize information for a block in one number, weighting all precision for all traits equally.
It is inversely proportional to standard errors.
Value
matrix of traces of information matrices, rows=persons, columns=blocks
susanne-frick/MFCblockInfo documentation built on Oct. 20, 2024, 8:26 p.m.
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View source: R/calc_info_trace.R
| calc.info.trace | R Documentation |
Trace of information matrix
Description
calculates the traits (= sum of diagonal elements) of the information matrix
Usage
calc.info.trace(infos, avg = F, prior = NULL)
Arguments
infos |
block information as returned from calc.info.block() |
avg |
logical, average result across persons? defaults to FALSE |
prior |
prior covariance matrix for the traits, defaults to NULL |
Details
This is the criterion of A-optimality used in computerized adaptive testing (CAT). It can be used to summarize information for a block in one number, weighting all precision for all traits equally. It is inversely proportional to standard errors.
Value
matrix of traces of information matrices, rows=persons, columns=blocks
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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