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Changelog

MBNMAtime 0.2.5

Additions/changes

  • SUCRA values generated by cumrank() now normalised to be between 0 and 1.
  • Allowed spline functions with up to 6 dose-response parameters

Bug fixes

  • When used with linear spline time-course functions (fun=tspline(type="ls")), predict() and get.relative() now ensure that the basis matrices comprise the entire duration of the available data in the model, rather than just the times specified in the times argument in predict()

MBNMAtime 0.2.4

CRAN release: 2023-10-14

Additions/changes

  • Reference SDs can now be used when modelling using SMDs to avoid using study-specific SDs which can lead to imprecision and heterogeneity.
  • 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.

Bug fixes

  • Error in nma.run when using link="smd" - a log link function was previously used but has now been fixed
  • Class models did not work properly with character class labels - now fixed

MBNMAtime 0.2.3

CRAN release: 2023-03-17

Additions/changes

  • Truncated priors are used as the default priors for time-course parameters that can only take positive values (e.g. et50) for all functions
  • texp() has been removed - titp() is a more stable parameterisation of this function

Bug fixes

Major

  • Error fixed preventing natural splines from functioning, causing removal from CRAN

Minor

  • Return values added to documentation for functions in which they were missing

MBNMAtime 0.2.2

Additions/changes

  • Can now specify numeric values for time-course parameters in the method argument. Can be useful for discrete values that cannot be estimated (e.g. fractional polynomial powers, Hill parameter).
  • Fractional polynomial powers in tfpoly() can only take numeric values from set defined in Jansen 2015.
  • Integrated Two-Component Prediction (ITP) function (titp()) added
  • get.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)
  • New priors that restrict posterior to positive values where necessary can be easily incorporated.
  • 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 parameter
  • corparam set to FALSE as default

Bug fixes

Minor

MBNMAtime 0.2.1

CRAN release: 2021-09-13

Additions/changes

  • get.relative() function can be used to calculate relative effects/mean differences between treatments/classes
  • cumrank() 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)
  • Studies reporting change from baseline or absolute means can now be specified in mb.network(), or will be automatically inferred from the data (studies with no time=0 are assumed to report change from baseline)
  • Model intercept (response at time=0) is now conditional on change from baseline for each study
  • texp() now implements 2-parameter exponential function (though the simpler 1-parameter model remains the default)

Bug fixes

Major

  • Error with predict() not properly incorporating absolute time-course parameters fixed

Minor

  • Error with model.file input length fixed for mb.run()

MBNMAtime 0.2.0

CRAN release: 2021-04-26

Additions/changes

  • Added variance adjustment (covar="varadj") for correlation between time-points - this is now the default in mb.run()
  • Added log linear time-course function (tloglin())
  • Added spline functions (piecewise linear splines, B-splines, restricted cubic splines, natural splines)
  • Added overlay.nma option to predict() to allow plotting of “lumped” NMA results over MBNMA predictions
  • Modelling can now incorporate Standardised Mean Differences (link="smd") or Ratios of Means (link="log") to allow modelling of studies with different scales
  • lower_better argument used instead of decreasing for rankings
  • Time-course functions given to mb.run() are now given as class("timefun") and time-course parameters are specified within these functions
  • Predictions from predict() can now be ranked
  • Forest plots now also plot posterior densities using ggdist::stat_halfeye()
  • Neater outputs when using print() or summary()
  • Wishart prior used to model correlations between within-study baseline effects on different time-course parameters, in addition to relative effects on different time-course parameters.

Bug fixes

Major

MBNMAtime 0.1.3

CRAN release: 2020-03-04

Additions/changes

  • Added citation file
  • 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())
  • Objects returned from 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 format

Bug fixes

Major

  • Exponential function models were not working previously but the dose-response function has been rewritten so that it runs the model correctly.
  • Ensured comparisons are cycled through correctly in mb.nodesplit
  • Ensured timeplot raw responses can be plotted by either arm (plotby="arm") or relative (plotby="rel") effects.

MBNMAtime 0.1.2

CRAN release: 2019-10-28

First release of package

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.