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]

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gemtcPlus.pdf |gemtcPlus.html✨
gemtcPlus/json (API)

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

Peer review:

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

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:

    On CRAN:

    evidence-synthesishealth-economic-evaluationhealth-economicshta

    49 exports 5 stars 0.82 score 110 dependencies 12 scripts

    Last updated 1 years agofrom:d6c4b4f1ad. Checks:OK: 1 ERROR: 6. Indexed: no.

    TargetResultDate
    Doc / VignettesOKAug 12 2024
    R-4.5-winERRORAug 12 2024
    R-4.5-linuxERRORAug 12 2024
    R-4.4-winERRORAug 12 2024
    R-4.4-macERRORAug 12 2024
    R-4.3-winERRORAug 12 2024
    R-4.3-macERRORAug 12 2024

    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:abindbackportsbase64encbitbit64bitopsbootbroombroom.helpersbslibcachemcaToolsclicliprcodacolorspaceCompQuadFormcpp11crayondigestdplyrevaluatefansifarverfastmapfontawesomeforcatsfsgemtcgenericsGGallyggmcmcggplot2ggstatsgluegplotsgtablegtoolshavenhighrhmshtmltoolsigraphisobandjquerylibjsonliteKernSmoothknitrlabelinglabelledlatticelifecyclelme4magrittrMASSmathjaxrMatrixmemoisemetametadatmetaformgcvmimeminqamunsellnetworknlmenloptrnumDerivpatchworkpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR2jagsR2WinBUGSR6rappdirsRColorBrewerRcppRcppEigenreadrreshapeRglpkrjagsrlangrmarkdownsassscalesslamstatnet.commonstringistringrtibbletidyrtidyselecttinytextruncnormtzdbutf8vctrsviridisLitevroomwithrxfunxml2yaml

    Bayesian FE & RE NMA for HR data (via gemtc package) - Result Generation

    Sandro Gsteiger, Nick Howlett

    Rendered fromexample-nma-hr-data.rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Bayesian FE & RE NMA using piecewise exponential model

    Sandro Gsteiger

    Rendered fromexample-nma-groupedTTE-PWE.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Bayesian FE fractional polynomial NMA for grouped survival data

    Sandro Gsteiger

    Rendered fromexample-nma-groupedTTE-FP.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Bayesian RE fractional polynomial NMA for grouped survival data

    Sandro Gsteiger

    Rendered fromexample-nma-groupedTTE-FP-RE.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Building Reports into the Package

    Nick Howlett, Sandro Gsteiger

    Rendered frombuilding-reports.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Building tests for your functions

    Nick Howlett, Sandro Gsteiger

    Rendered frombuilding-tests.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    Documenting Functions

    Nick Howlett, Sandro Gsteiger

    Rendered fromdocumenting-functions.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    General Development Workflow

    Nick Howlett, Sandro Gsteiger

    Rendered fromgeneral-development-workflow.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    NMA for Binary data (2-arm trials)

    Beth Ashlee

    Rendered fromexample-nma-binary-data.Rmdusingknitr::rmarkdownon Aug 12 2024.

    Last update: 2021-10-22
    Started: 2021-10-22

    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
    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