Package: gemtcPlus 1.0.0

Sandro Gsteiger

gemtcPlus: Provides a suite of extension functions for NMA using the `gemtc` package

Functions for generating outputs: tables and plots for NMA reports.

Authors:Sandro Gsteiger [aut, cre], Nick Howlett [aut], Beth Ashlee [aut], F. Hoffmann La Roche Ltd [cph]

gemtcPlus_1.0.0.tar.gz
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gemtcPlus_1.0.0.tgz(r-4.6-any)gemtcPlus_1.0.0.tgz(r-4.5-any)
gemtcPlus_1.0.0.tar.gz(r-4.7-any)gemtcPlus_1.0.0.tar.gz(r-4.6-any)
gemtcPlus_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gemtcPlus/json (API)

# Install 'gemtcPlus' in R:
install.packages('gemtcPlus', repos = c('https://pharmaverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/roche/gemtcplus/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

evidence-synthesishealth-economic-evaluationhealth-economicshtajagscpp

3.03 score 6 stars 12 scripts 49 exports 106 dependencies

Last updated from:55fede3379. Checks:8 ERROR, 1 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR185
source / vignettesERROR482
linux-release-x86_64ERROR175
macos-release-arm64ERROR155
macos-oldrel-arm64ERROR145
windows-develERROR132
windows-releaseERROR156
windows-oldrelERROR149
wasm-releaseOK145

Exports:bth_priorcreate_templateget_fp_1oget_fp_1o_GoFget_fp_1o_HRget_fp_1o_Sget_fp_2oget_fp_2o_GoFget_fp_2o_HRget_fp_2o_Sget_fp_comparisonget_fp_contrastsget_fp_corrsget_fp_elementsget_fp_GoFget_fp_HRget_fp_Sget_jags_infoget_mtc_allVsNewget_mtc_newVsAllget_mtc_probBetterget_mtc_sumget_nw_fromtoget_pw_segmentsget_pwe_comparisonget_pwe_contrastsget_pwe_conv_diagget_pwe_elementsget_pwe_GoFget_pwe_Sget_segmentsgroupedTTE_fp_pre_procgroupedTTE_pwe_pre_proclist_BUGSmatch_args_to_funcmtc.prob.better.tablenma_fitnma_pre_procplan_binaryplan_fpplan_hrplan_pweplot_fp_HRplot_mtc_forestprocess_binaryprocess_gsdprocess_hrpwe_Hupwe_S

Dependencies:abindbase64encbitbit64bitopsbootbslibcachemcaToolsclicliprcodaCompQuadFormcpp11crayondigestdplyrevaluatefarverfastmapfontawesomeforcatsfsgemtcgenericsGGallyggmcmcggplot2ggstatsgluegplotsgtablegtoolshighrhmshtmltoolsigraphisobandjquerylibjsonliteKernSmoothknitrlabelinglatticelifecyclelme4magrittrMASSmathjaxrMatrixmemoisemetametabookmetadatmetaformimeminqanetworknlmenloptrnumDerivpatchworkpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR2jagsR2WinBUGSR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasreshapeRglpkrjagsrlangrmarkdownS7sassscalesslamstatnet.commonstringistringrtibbletidyrtidyselecttinytextruncnormtzdbutf8vctrsviridisLitevroomwithrxfunxml2yaml

Readme and manuals

Help Manual

Help pageTopics
Creates a fractional polynomial model planbth_prior
create_jags_init. Helper function to create jags init list dependant on length on chains providedcreate_jags_init
Creates a minimal project template for selected model typecreate_template
Helper function to extract BUGS files for given input parametersextract_BUGS_file
gemtcPlus: A package for performing NMA in RgemtcPlus-package gemtcPlus
First order fractional polynomialget_fp_1o
Calculate the study and arm level survivor functions estimates from a 1st order fractional polynomial NMA. These estimates provide the basis for a goodness-of-fit graph when plotted along with the input data.get_fp_1o_GoF
Calculate the time-dependent hazard ratios obtained from fitting a first order fractional polynomial model.get_fp_1o_HR
Calculate the survivor functions estimated in a 1st order fractional polynomial NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the fractional polynomial (log)hazard ratio estimates to construct the S(t) functions for each treatment.get_fp_1o_S
Second order fractional polynomialget_fp_2o
Calculate the study and arm level survivor functions estimates from a 2nd order fractional polynomial NMA. These estimates provide the basis for a goodness-of-fit graph when plotted along with the input data.get_fp_2o_GoF
Calculate the time-dependent hazard ratios obtained from fitting a second order fractional polynomial model.get_fp_2o_HR
Calculate the survivor functions estimated in a 2nd order fractional polynomial NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the fractional polynomial (log)hazard ratio estimates to construct the S(t) functions for each treatment.get_fp_2o_S
Extract model information and fit statistics from a list of fractional polynomial NMAs.get_fp_comparison
Extract the treatment contrasts vs the reference in the networkget_fp_contrasts
Calculate correlations between the contrast estimates for multi-dimensional effect estimates for all treatments in a FP NMA.get_fp_corrs
Extract model information and fit statistics from NMA fit in jags of a fractional polynomial model.get_fp_elements
Calculate the study and arm level survivor functions estimates from a fractional polynomial NMA. These estimates provide the basis for a goodness-of-fit graph when plotted along with the input data.get_fp_GoF
Calculate the time-dependent hazard ratios obtained from fitting a fractional polynomial model (first or second order).get_fp_HR
Calculate the survivor functions estimated in a fractional polynomial NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the fractional polynomial (log)hazard ratio estimates to construct the S(t) functions for each treatment.get_fp_S
Utility function to return jags data and model for reporting (e.g. in appendix)get_jags_info
Utility function to extract effect estimates "other treatments vs new" from gemtc fit.get_mtc_allVsNew
Utility function to extract effect estimates "new vs other treatments" from gemtc fit.get_mtc_newVsAll
Utility function to extract probabilities of new treatment being better from gemtc fit (e.g. P(HR<1) for HRs new vs other).get_mtc_probBetter
Utility function to extract summary stats from mtc.result object.get_mtc_sum
Extract edges information ("from-to matrix") from network data frame.get_nw_fromto
Utility function to get segments (as character strings) from vector with cutpointsget_pw_segments
Extract model information and fit statistics from a list of piecewise-exponential NMA fits.get_pwe_comparison
Utility function to extract HR estimates from piece-wise exponential model fit in (format needed for ggplot)get_pwe_contrasts
Utility function: convergence diagnostics for piece-wise constant modelsget_pwe_conv_diag
Extract model information and fit statistics from NMA fit in jags of a piecewise-exponential model.get_pwe_elements
Calculate the survivor function estimates for each study and arm. Calculate also the observed survival curves from the binned KM data to compare observed and estimated survivor functions.get_pwe_GoF
Calculate the survivor functions estimated in piecewise-constant NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the piecewise-constant hazard ratio estimates to construct the S(t) functions for each treatment.get_pwe_S
Utility function to get segments (as character strings) from vector with cutpointsget_segments
Utility function for pre-processing: prepare jags input data for FP model.groupedTTE_fp_pre_proc
Utility function for pre-processing: prepare jags input data for PWE model.groupedTTE_pwe_pre_proc
Lists all available model files inside the inst directorylist_BUGS
Helper function to extract named elements from a list to match the arguments of supplied functionmatch_args_to_func
Utility function providing pairwise probability of being better (col vs row). (Adapted from gemtc::relative.effect.table()).mtc.prob.better.table
Takes input data and a model plan and passes to the model engine specified. Current supported engines are the `gemtc` package (using mtc.model & mtc.run) or `rjags` (using jags and dic.samples functions)nma_fit
NMA data pre-processingnma_pre_proc
Creates a model plan for binary dataplan_binary
Creates a fractional polynomial model planplan_fp
Creates a model plan for hazard ratioplan_hr
Creates a fractional polynomial model planplan_pwe
Produce ggplot from HR values in data.frame (medians vs time for several trts, all in one plot)plot_fp_HR
Utility function to do forest plot from data.frame with effect estimates.plot_mtc_forest
Transforms binary dataprocess_binary
Transforms grouped survival dataprocess_gsd
Transforms hazard ratio dataprocess_hr
Calculate the cumulative hazard over [0, tmax] from piecewise constant model.pwe_Hu
Calculate the survivor function S(t) from a piecewise exponential model.pwe_S