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Bin data on one time scale

Source: R/exposures_events_1d.R
exposures_events_1d.Rd

exposure_events_1d() computes aggregated measures of exposure times and event counts starting from individual records of time at entry, time at exit and event's indicator, over one time scale (s).

Usage

exposures_events_1d(s_in = NULL, s_out, ev, bins)

Arguments

s_in

A vector of (possibly left truncated) times at entry. If this is not provided by the user, the function will consider a value of 0 for all observations.

s_out

A vector of times at event or censoring.

ev

A vector of events' indicators (possible values 0/1).

bins

A vector of interval breaks for discretization (see also make_bins()).

Value

A list with the following elements:

  • R A matrix of dimension \(n\) by \(ns\) containing the exposure times for each individual separately.

  • r A vector of exposure times.

  • Y A matrix of dimension \(n\) by \(ns\) containing the event counts for each individual separately

  • y A vector of event counts.

If the length of the input vectors do not match, an error message is returned.

Details

The time scale s is divided into bins of equal size, which are provided as input to the function. Then, the time-at-risk for each individual is split according to these bins, and an event indicator is placed in the bin where the exit time is located. Finally, the individual contributions are summed in each bin to provide a vector of total exposure time and total event counts. See also prepare_data() to conveniently prepare individual data for the analysis with one, or two time scales.

Author

Angela Carollo carollo@demogr.mpg.de and Paul Eilers p.eilers@erasmus.nl

Examples

# ---- Bin colon cancer data by time since recurrence ----
# First create vector of bins
bins1ts <- make_bins(s_in = reccolon2ts$entrys, s_out = reccolon2ts$timesr, ds = 30)
bindata <- exposures_events_1d(s_in = reccolon2ts$entrys,
s_out = reccolon2ts$timesr, ev = reccolon2ts$status, bins = bins1ts$bins_s)