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NEWS for Dire
Changes in version 2.2.0
Methods update
Functions are a bit clearer about some errors when data sets do not agree. In particular, when a PSU/stratum variable is missing and
Taylorvariance is selected it gives a plain language error.turning on
multiCorenow fits the latent regressions with multiple cores too. Previously it would only fit the covariance matrix with multiple cores.added a nearly singular model check
allow
stuDatto have students that are not on the item data without throwing an error.optimization tries to avoid Newton's method by using the
lbfgspackage which allows for a condition on the gradient to be set. Newton's method can be very slow for large datasets.when Newton's method is used, the output is more verbose.
the C++ implementation of the Hessian has been sped up a bit.
Changes in version 2.1.1
BUG FIXES
Fixed bug in degrees of freedom replication in composite. This causes summary to fail in many cases.
Fixed version number error in this file. 2.1.0 changes had previously been named 2.0.0.
Changes in version 2.1.0
New features
Added degrees of freedom and p-values to
mmlresults-
mmlshould be faster now
Changes in version 2.0.0
New features
Added
drawPVfunctions that draw plausible values from a normal approximation to the posterior distribution. See thedrawPVsfunction help for details.the object returned by
mmlnow includes an objectitemScorePointsthat shows, for each item, the expected and actually occupied score points.If items have invalid score points an error now shows the
itemScorePointstable.
Methods update
The
mmlfunction used to use the bobyqa optimizer and now uses a combination of theoptimfunction and then a Newton's method optimizerThe
mmlfunction Taylor series covariance calculation for composite results has been updated so that the correlation is calculated for all subscales simultaneously. This results in covariance matrix that is always positive definite. The old method can be used by requesting "Partial Taylor".