Package index • BayesianQDM

Designs

Specification of a proof-of-concept study

design_binary(): Design with one binary endpoint
design_continuous(): Design with one continuous endpoint
design_binary2(): Design with two binary endpoints
design_continuous2(): Design with two continuous endpoints
design_tte(): Design with one time-to-event endpoint
conduct_tte(): Conduct of a study with a time-to-event endpoint

Operations

Decision for observed data, operating characteristics, calibration of the thresholds and decision boundaries

qdm_decide(): Go/NoGo decision for observed data
qdm_oc(): Operating characteristics of a design
qdm_calibrate(): Calibration of the decision thresholds
qdm_boundary(): Decision boundary of a design

Priors

Prior distributions of each group

prior_beta(): Beta prior for a response rate
prior_nix(): Normal-Inverse-chi-squared prior for a continuous endpoint
prior_dirichlet(): Dirichlet prior for two binary endpoints
prior_niw(): Normal-Inverse-Wishart prior for two continuous endpoints
prior_gamma(): Gamma prior for a hazard rate
prior_vague(): Vague prior for continuous endpoints

Data, external data and hypothetical controls

Summaries of the data of one group, external data borrowed through a power prior, and hypothetical controls

data_binary(): Binary endpoint data
data_continuous(): Continuous endpoint data
data_binary2(): Data for two binary endpoints
data_continuous2(): Data for two continuous endpoints
data_tte(): Time-to-event endpoint data
borrow(): External data borrowed through a power prior
hypothetical(): Hypothetical control for an uncontrolled study

Decision criteria

Criteria based on posterior and posterior predictive probabilities

criterion_posterior(): Decision criterion based on posterior probability
criterion_predictive(): Decision criterion based on posterior predictive probability
qdm_regions(): Region numbers for two endpoints

Distribution functions

Distribution functions and random generation used by the decision criteria

pbetadiff(): Distribution function of the difference of two Beta variables
pbetabinomdiff(): Distribution function of the difference of two Beta-binomial proportions
ptdiff(): Distribution function of the difference of two t variables
psurvdiff(): Distribution function of the difference of two milestone survival probabilities
phazardratio(): Distribution function of the ratio of two hazards
cellprob_binary2(): Joint cell probabilities of two binary endpoints
rdirichlet(): Random generation from the Dirichlet distribution

Print, format and plot methods

print(<qdm_borrow>): Print an external data specification
print(<qdm_boundary>): Print a decision boundary
print(<qdm_calibration>): Print a calibration
print(<qdm_conduct>): Print the conduct of a study
print(<qdm_criterion>): Print a decision criterion
print(<qdm_data>): Print a data specification
print(<qdm_decision>): Print a decision
print(<qdm_design>): Print a design
print(<qdm_hypothetical>): Print a hypothetical control specification
print(<qdm_oc>): Print operating characteristics
print(<qdm_prior>): Print a prior specification
format(<qdm_borrow>): Format an external data specification
format(<qdm_boundary>): Format a decision boundary
format(<qdm_calibration>): Format a calibration
format(<qdm_conduct>): Format the conduct of a study
format(<qdm_criterion>): Format a decision criterion
format(<qdm_data>): Format a data specification
format(<qdm_decision>): Format a decision
format(<qdm_design>): Format a design
format(<qdm_hypothetical>): Format a hypothetical control specification
format(<qdm_prior>): Format a prior specification
plot(<qdm_boundary>): Plot a decision boundary
plot(<qdm_calibration>): Plot a calibration
plot(<qdm_oc>): Plot operating characteristics