A simple logistic exposure survival simulation.

simulate logistic exposure survival data, returns a "long" object with n.individuals X n observations rows or a 'wide' object for a different analysis method. permits right censoring

Usage

sim1_logexp(
  S.int = 0.95,
  nind = 10,
  ntime = 10,
  p.obs = 0.5,
  obs.start = TRUE,
  r.censor = FALSE,
  p.censor = 0.1,
  t.censor = 0.8,
  cjs = FALSE,
  logexp = TRUE
)

Arguments

S.int: the interval survival probability
nind: the number of individuals
ntime: the length of the encounter histories
p.obs: a probability to create differences in exposure period
obs.start: TRUE or FALSE, if true, all individuals are observed at time =1, otherwise. all individuals may not be observed until later in their encounter history, or not at all before failing
r.censor: TRUE or FALSE, the probability an individual is right censored. The function defaults to having all individuals observed at the last time interval (as is typical in nest survival studies)
p.censor: the probability an individual is right censored before time = ntime
t.censor: controls when censoring occurs by treating censoring time as a binomial process where the number of trials is the length of the encounter history and t.censor is the probability, and the resulting number of successes is the interval at which censoring occurs
cjs: if TRUE, the encounter history is output in a matrix typical of CJS matrix, suitable for use in a bayesian frameowrk
logexp: of TRUE, returns a data frame of rows of individual observation intervals for use in glm or similar

Value

with logexp = TRUE, a data frame of nest-visits with the interval between visits in a separate column.

Examples

# Show a long-format survival data set using the above defaults
if (FALSE) { # \dontrun{

sim1_logexp(r.censor=TRUE,p.censor=0.2)->sim.dat

} # }