rank.mbnma()
can now only rank a single parameter
(e.g. param
argument must be length 1). This facilitates
differentiation between treatment and class parameters.link="smd"
- a log link
function was previously used but has now been fixedet50
)
for all functionstexp()
has been removed - titp()
is a more
stable parameterisation of this functionmethod
argument. Can be useful for discrete values that
cannot be estimated (e.g. fractional polynomial powers, Hill
parameter).tfpoly()
can only take
numeric values from set defined in Jansen 2015.titp()
) addedget.relative()
can be used to combine two MBNMA models
to allow different time-course functions to be fitted to a different set
of treatments (see examples in the vignette)binplot()
can be used to plot the results of NMAs
conducted at multiple time bins. This can be particularly useful to
explore which time-course functions might be appropriate, and to check
the validity of MBNMA predictions.mb.nodesplit()
can be performed at specific
time-points, in addition to by time-course parametercorparam
set to FALSE
as defaultoverlay.nma
argument in
plot.mb.predict()
fixedget.relative()
function can be used to calculate
relative effects/mean differences between treatments/classescumrank()
added for cumulative ranking plots. Also
calculates SUCRA values for each treatment and time-course parameter at
specified follow-up times (even those at which treatments have not been
compared within any study)mb.network()
, or will be automatically
inferred from the data (studies with no time=0 are assumed to report
change from baseline)texp()
now implements 2-parameter exponential function
(though the simpler 1-parameter model remains the default)predict()
not properly incorporating
absolute time-course parameters fixedmodel.file
input length fixed for
mb.run()
covar="varadj"
) for
correlation between time-points - this is now the default in
mb.run()
tloglin()
)overlay.nma
option to predict()
to
allow plotting of “lumped” NMA results over MBNMA predictionslink="smd"
) or Ratios of Means (link="log"
)
to allow modelling of studies with different scaleslower_better
argument used instead of
decreasing
for rankingsmb.run()
are now given
as class("timefun")
and time-course parameters are
specified within these functionspredict()
can now be rankedggdist::stat_halfeye()
print()
or
summary()
mb.nodesplit()
plot.mb.network()
now uses a layout
argument that takes an igraph layout function instead of
layout_in_circle
(which was a logical argument). This
allows any igraph layout to be plotted rather than just a circle
(e.g. igraph::as_star()
)plot.mb.network
now have specific
igraph attributes assigned to them, which can be easily changed by the
user.user.fun
now takes a formula as an argument (for
example ~ (beta.1 * dose) + (beta.2 * dose^2)
) rather than
a string.mb.network
objects are now stored within lists of most
other mb class objects for easy reference of data formattimeplot
raw responses can be plotted by either
arm (plotby="arm"
) or relative (plotby="rel"
)
effects.Welcome to MBNMAtime. Ready for release into the world. I hope it can be of service to you! For dose-response MBNMA, also check out the sister package, MBNMAdose.