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glsPower() now supports count outcomes via
family="poisson"icc_to_RandEff(), RandEff_to_icc(),
RandEff_to_alpha012(), and
alpha012_to_RandEff() for converting between random effects
variances and ICC/CAC/IAC parametersglsPower(), the argument N now
overrides the N stored in a supplied DesMat
objectglsPower() now fails gracefully (with a warning) if the
information content cannot be calculateddsntype,
family) now throw an error if no known option is
sufficiently similar, instead of silently choosing the closest
matchmessage() instead of
print()fbdiag
(fast block diagonal matrix)plot_CellWeights() now treats NA entries
in incompMat as unobserved cluster periods\() with function() for backward
compatibility with older R versionsRandEff_to_alphaconstruct_DesMat(),
construct_CovMat(), and glsPower()N (subjects per cluster-period cell) now belongs to
DesMat classNA in incompMat and
trtMatwls (weighted least squares) in function names is now
replaced with gls (generalised least squars) to more
properly reflect the scope of the functionality. For example, the
function wlsPower() is now called glsPower() -
although the former version still works and throws a warning.compute_InfoContent()plot.glsPower() there now is an option to manually
set the font size of the annotation in the influence plotswlsPower() now also computes the
information content of cluster-period cells. Computation is currently
done twice, once with a general formula and once explicitly. Information
content of whole periods or clusters is also computed.plot.wlsPower() recieved multiple updates:
annotations = <TRUE/FALSE>show_colorbar to hide colour bars was
addedmarginal_plots to hide marginal plots on
whole periods or clusters was added.wlsPower() now has an argument
alpha_012 that offers an alternative way to specifiy the
correlation matrix.wlsPower(), the argument AR
now accepts a vector of up to three values. This allows to specifiy
autoregressive structures for only a subset of: random cluster
intercept, random intervention effect and random subject intercept.plot.wlsPower now produces up to three
plots, the projection matrix, the intervention design and the covariance
matrix.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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