Package index • carts

All functions

Trial: R6 class for power and sample-size calculations for a clinical trial

aggrsurv(): Aggregate data in counting process format

`append<-`(<list>): Assignment function to append values to existing list

bisection(): Root finding by bisection

covar_add(): Add additional covariates to existing list of covariates

covar_bootstrap(): Sample from empirical distribution of covariate data

covar_join(): Add additional covariates to existing covariate random generator

covar_loggamma(): Simulate from a log gamma-gaussian copula distribution

covar_normal(): Simulate from multivariate normal distribution

derive_covar_distribution(): Derive covariate distribution from covariate data type

est_adj(): Construct estimator for the treatment effect in RCT based on covariate adjustment

est_glm(): Construct estimator for the treatment effect in RCT

est_phreg(): Marginal Cox proportional hazards model for the treatment effect in RCT

estimate_covar_model_full_cond(): Full conditional covariate simulation model

get_factor_levels(): Get levels for factor columns in data.table

optim_sa(): Root solver by Stochastic Approximation

outcome_binary(): Simulate from binary model given covariates

outcome_continuous(): Simulate from continuous outcome model given covariates

outcome_count(): Simulate from count model given covariates

outcome_lp(): Calculate linear predictor from covariates

outcome_phreg(): Outcome model for time-to-event end-points (proportional hazards)

outcome_recurrent(): EXPERIMENTAL: Outcome model for recurrent events with terminal events end-points

outcome_shared: Outcome model

rmvn(): Multivariate normal distribution function

rnb(): Simulate from a negative binomial distribution

sample_covar_parametric_model(): Sample from an estimated parametric covariate model

setargs(): Set default arguments of a function

trial.estimates-class: trial.estimates class object