High-Performance Open-Source Archive
All Cat objects are reverted to the bounds of
[-5,5]. Likewise, the Cat class defaults are now
[-5,5].
Newton Raphson bug fixed. Bug was causing estimates when no questions have been answered to go to extremes rather than prior mean.
simulateThetas() has a new argument (defaulted to
FALSE for backwards compatibility) that when TRUE returns a list of
dataframes containing adaptive answer profiles for each Cat objected
involved in the simulation
All Cat objects now use integration bounds of
[-4,4]. Likewise, the Cat class defaults are now [-4,4].
This narrows the bounds of integration from [-5,5] to avoid
computational issues that arise at “extreme” values of the latent
trait.
Cat object z slot still defaults to .9,
but now in calculating delta for certain integration routines, the
package executes qnorm(z).
oracle() function adds option for parallel computing
using plyr
probability() for categorical data now throws errors
to account for extreme values of latent trait that may cause
computational issues
simulateRespondents() bug fix when respondent’s
answer in raw data is NA, now transform to -1 to indicate a
skip
added dataset of Need to Evaluate raw response profiles
readQualtrics() now has respondent ID as rownames
instead of a column.
Added example data for the readQualtrics()
function.
New functions simulateRespondents(),
simulateThetas(), simulateFisherInfo(), and
oracle() allow for simulation exercises to evaluate model
quality and performace.
New function plot.Cat() allows for visual
representation of item parameters.
New functions fromJSONCat(),
toJSONCat(), and readQualtrics() aid the user
in creating an adaptive battery in Qualtrics using
catSurv.
The slot ids was added to the Cat
object representing each question item’s unique identifier.
selectItem() returns a third item,
next_item_name which represents the unique identifier of
the item that should be asked next.
lookAhead() now returns the next best item given the
question is skipped.
estimateThetas() and
simulateThetas() allow for estimation of ability parameter
for dataframe of response sets.checkStopRules().selectItem().ltmCat(), tpmCat(),
grmCat(), and gpcmCat() by adding the
ltm package to Imports.stats and methods
imports as it caused errors in testing with r-oldrel.
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