Parametric Time-to-Event Analysis with Variable Incubation Phases
Refit an incubate_fit-object with specified optimization arguments. ...
Format a number as percentage.
Generate bootstrap distribution of model parameters to fitted incubate...
Coefficients of a delay-model fit.
Confidence intervals for parameters of incubate-model fits.
Fit optimal parameters according to the objective function (either MPS...
Fit a delayed Exponential or Weibull model to one or two given sample(...
Delayed Exponential Distribution
Delayed Weibull Distribution
Estimate rounding error based on given sample of metric values The ide...
Get delay distribution function
Incubate package for parametric time-to-event analysis with delay
Minimize an objective function with PORT routine (nlminb)
Factory method for objective function, either according to maximum pro...
Power simulation function for a two-group comparison of the delay para...
Calculate parameter scaling for optimization routine.
Test the difference for delay model parameter(s) between two uncorrela...
Goodness-of-fit (GOF) test statistic.
Transform observed data to unit interval
Fit parametric models for time-to-event data that show an initial 'incubation period', i.e., a variable delay phase where the hazard is zero. The delayed Weibull distribution serves as foundational data model. The specific method of 'MPSE' (maximum product of spacings estimation) and MLE-based methods are used for parameter estimation. Bootstrap confidence intervals for parameters and significance tests in a two group setting are provided.