Function reference • gemtcPlus

All functions
`bth_prior()`	Creates a fractional polynomial model plan
`create_jags_init()`	create_jags_init. Helper function to create jags init list dependant on length on chains provided
`create_template()`	Creates a minimal project template for selected model type
`extract_BUGS_file()`	Helper function to extract BUGS files for given input parameters
`gemtcPlus`	gemtcPlus: A package for performing NMA in R
`get_fp_1o()`	First order fractional polynomial
`get_fp_1o_GoF()`	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_HR()`	Calculate the time-dependent hazard ratios obtained from fitting a first order fractional polynomial model.
`get_fp_1o_S()`	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_2o()`	Second order fractional polynomial
`get_fp_2o_GoF()`	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_HR()`	Calculate the time-dependent hazard ratios obtained from fitting a second order fractional polynomial model.
`get_fp_2o_S()`	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_GoF()`	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_HR()`	Calculate the time-dependent hazard ratios obtained from fitting a fractional polynomial model (first or second order).
`get_fp_S()`	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_comparison()`	Extract model information and fit statistics from a list of fractional polynomial NMAs.
`get_fp_contrasts()`	Extract the treatment contrasts vs the reference in the network
`get_fp_corrs()`	Calculate correlations between the contrast estimates for multi-dimensional effect estimates for all treatments in a FP NMA.
`get_fp_elements()`	Extract model information and fit statistics from NMA fit in jags of a fractional polynomial model.
`get_jags_info()`	Utility function to return jags data and model for reporting (e.g. in appendix)
`get_mtc_allVsNew()`	Utility function to extract effect estimates "other treatments vs new" from gemtc fit.
`get_mtc_newVsAll()`	Utility function to extract effect estimates "new vs other treatments" from gemtc fit.
`get_mtc_probBetter()`	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_sum()`	Utility function to extract summary stats from mtc.result object.
`get_nw_fromto()`	Extract edges information ("from-to matrix") from network data frame.
`get_pw_segments()`	Utility function to get segments (as character strings) from vector with cutpoints
`get_pwe_GoF()`	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_S()`	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_comparison()`	Extract model information and fit statistics from a list of piecewise-exponential NMA fits.
`get_pwe_contrasts()`	Utility function to extract HR estimates from piece-wise exponential model fit in (format needed for ggplot)
`get_pwe_conv_diag()`	Utility function: convergence diagnostics for piece-wise constant models
`get_pwe_elements()`	Extract model information and fit statistics from NMA fit in jags of a piecewise-exponential model.
`get_segments()`	Utility function to get segments (as character strings) from vector with cutpoints
`groupedTTE_fp_pre_proc()`	Utility function for pre-processing: prepare jags input data for FP model.
`groupedTTE_pwe_pre_proc()`	Utility function for pre-processing: prepare jags input data for PWE model.
`list_BUGS()`	Lists all available model files inside the inst directory
`match_args_to_func()`	Helper function to extract named elements from a list to match the arguments of supplied function
`mtc.prob.better.table()`	Utility function providing pairwise probability of being better (col vs row). (Adapted from gemtc::relative.effect.table()).
`nma_fit()`	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_pre_proc()`	NMA data pre-processing
`plan_binary()`	Creates a model plan for binary data
`plan_fp()`	Creates a fractional polynomial model plan
`plan_hr()`	Creates a model plan for hazard ratio
`plan_pwe()`	Creates a fractional polynomial model plan
`plot_fp_HR()`	Produce ggplot from HR values in data.frame (medians vs time for several trts, all in one plot)
`plot_mtc_forest()`	Utility function to do forest plot from data.frame with effect estimates.
`process_binary()`	Transforms binary data
`process_gsd()`	Transforms grouped survival data
`process_hr()`	Transforms hazard ratio data
`pwe_Hu()`	Calculate the cumulative hazard over [0, tmax] from piecewise constant model.
`pwe_S()`	Calculate the survivor function S(t) from a piecewise exponential model.

Reference

All functions