Function reference • tipmap

All functions

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