R: Tipping Point Analysis for Bayesian Dynamic Borrowing

# Tipping Point Analysis for Bayesian Dynamic Borrowing

## Documentation for package ‘tipmap’ version 1.0.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

create_new_trial_data | Data on new trial in target population
create_posterior_data | Quantiles of 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