Tipping Point Analysis for Bayesian Dynamic Borrowing


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Documentation for package ‘tipmap’ version 0.5.2

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_nsamples Draw 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_summary_mult_exp Summarize expert weights
get_tipping_points Identify tipping point for a specific quantile.
load_tipmap_data Load exemplary datasets
oc_bias Assessing bias
oc_coverage Assessing coverage
oc_pos Assessing probability of success
tipmap_darkblue Custom dark blue
tipmap_lightred Custom light red
tipmap_plot Visualize tipping point analysis