run_sample_times_simulations: Runs multiple simulations for infection time by ID and given...

In bryanmayer/multdr: Simulating and fitting multiple exposure infectious disease dose-response models

Description

This function takes data of multiple subjects with repeated exposure data and runs mulitple stochastic simulations estimating infection time infection time that is linked to the given detection time. For more flexibility on returning exact infection times, use TBD.

Usage

run_sample_times_simulations(nsims = 100, raw_exposure_data, raw_sample_times,
  exposure_rate, hazard_risk, clr = 2, lag = 0, return_KM = F,
  parallel = F)

Arguments

raw_exposure_data	The data.frame time containing series of all possible exposures (must include a day and count name) for all subjects (FamilyID)
raw_sample_times	The sampling days that infection would actually be observed for each subject
exposure_rate	The rate of exposures to be sampled from raw_exposure_data
hazard_risk	The per time hazard risk for the hazard function
clr	The exponential pathogen clearance rate
lag	The minimum amount of time between infection and when it could be detected (lag = 0 means infection is instantly detectable)
return_KM	return the Kaplan-Meier estimates from all the runs (if false, just returns raw data)
parallel,	Use parallel computation for simulations across nsim
nsim	The amount of simulations to run

Value

Either a data.frame of infection time simulations for each family matched to sample times or a Kaplan-Meier object

bryanmayer/multdr documentation built on May 13, 2019, 8:11 a.m.