generate_presence: Simulate incidence in the presence of screening.

In roman-gulati/overdiag: A package to investigate empirical estimates of overdiagnosis

Description

Screen a simulated population using specified sensitivity and count screen diagnoses in each year of screening for relevant disease that develops in each year with a given sojourn time.

Usage

generate_presence(dset, sojourn.min, sojourn.max, sensitivity, attendance,
  screen.start.year, screen.stop.year, followup.years)

Arguments

dset	A data frame of simulated population as produced by generate_absence.
sojourn.min	Minimum years of preclinical detectable period.
sojourn.max	Maximum years of preclinical detectable period.
sensitivity	Proportion of relevant disease detected by screening.
attendance	Proportion of individuals who attend screening tests.
screen.start.year	Year of follow-up at which screening starts.
screen.stop.year	Year of follow-up at which screening stops.
followup.years	Number of years of follow-up.

Value

A data frame of simulated disease incidence organized by year of preclinical onset, sojourn time, and year of clinical diagnosis.

See Also

generate_absence, generate_overdiag

Examples

library(plyr)
library(reshape)
dset <- generate_absence(1000, 0.001, 0, 6, 10)
dset <- generate_presence(dset, 0, 6, 0.5, 0.8, 0, 10, 10)
print(head(dset))

roman-gulati/overdiag documentation built on May 27, 2019, 1:49 p.m.