Tipping Point Analysis for Bayesian Dynamic Borrowing

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Documentation for package ‘tipmap’ version 0.3.9

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

create_new_trial_data	Data on new trial in target population
create_posterior_data	Creates posterior distributions for a range of weights on the informative component of the robust MAP prior
create_prior_data	Creates input data frame for construction of MAP prior
create_tipmap_data	Create data frame ready to use for tipping point analysis
default_quantiles	Default quantiles
default_weights	Default weights
draw_beta_mixture_1sample	Draw a single sample from a mixture of beta distributions
draw_beta_mixture_nsamples	Draw n samples from a mixture of beta distributions
fit_beta_1exp	Fit beta distribution for one expert
fit_beta_mult_exp	Fit beta distributions for multiple experts
get_cum_probs_1exp	Get cumulative probabilities from distribution of chips of one expert
get_model_input_1exp	Transform cumulative probabilities to fit beta distributions
get_posterior_by_weight	Filter posterior by given weights
get_stochast_weight_posterior	Computation of posterior distribution using weights sampled from a distribution of weights
get_summary_mult_exp	Summarize expert weights
get_tipping_points	Identify tipping point for a specific quantile.
load_tipmap_data	Load exemplary datasets
tipmap_darkblue	Custom dark blue
tipmap_lightred	Custom light red
tipmap_plot	Visualize tipping point analysis