simulate_interval_censoring {rwicc}

Simulate a dataset with interval-censored seroconversion dates

Description

simulate_interval_censoring generates a simulated data set from a data-generating model based on the typical structure of a cohort study of HIV biomarker progression, as described in Morrison et al (2021); doi: 10.1111/biom.13472.

Usage

simulate_interval_censoring(
  study_cohort_size = 4500,
  hazard_alpha = 1,
  hazard_beta = 0.5,
  preconversion_interval_length = 84,
  theta = c(0.986, -3.88),
  probability_of_ever_seroconverting = 0.05,
  years_in_study = 10,
  max_scheduling_offset = 7,
  days_from_study_start_to_recruitment_end = 365,
  study_start_date = lubridate::ymd("2001-01-01")
)

Arguments

study_cohort_size

the number of participants to simulate (N_0 in the paper)

hazard_alpha

the hazard (instantaneous risk) of seroconversion at the start date of the cohort study for those participants at risk of seroconversion

hazard_beta

the change in hazard per calendar year

preconversion_interval_length

the number of days between tests for seroconversion

theta

the parameters of a logistic model (with linear functional from) specifying the probability of MAA-positive biomarkers as a function of time since seroconversion

probability_of_ever_seroconverting

the probability that each participant is at risk of HIV seroconversion

years_in_study

the duration of follow-up for each participant

max_scheduling_offset

the maximum divergence of pre-seroconversion followup visits from the prescribed schedule

days_from_study_start_to_recruitment_end

the length of the recruitment period

study_start_date

the date when the study starts recruitment ("d_0" in the main text). The value of this parameter does not affect the simulation results; it is only necessary as a reference point for generating E, L, R, O, and S.

Value

A list containing the following two tibbles:

• pt_data: a tibble of participant-level information, with the following columns:

  • ID: participant ID

  • E: enrollment date

  • L: date of last HIV test prior to seroconversion

  • R: date of first HIV test after seroconversion

• obs_data: a tibble of longitudinal observations with the following columns:

  • ID: participant ID

  • O: dates of biomarker sample collection

  • Y: MAA classifications of biomarker samples

References

Morrison, Laeyendecker, and Brookmeyer (2021). "Regression with interval-censored covariates: Application to cross-sectional incidence estimation". Biometrics. doi: 10.1111/biom.13472.

Examples

study_data <- simulate_interval_censoring()
participant_characteristics <- study_data$pt_data
longitudinal_observations <- study_data$obs_data