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Bin data on the Lexis diagram

Source: R/exposures_events_Lexis.R
exposures_events_Lexis.Rd

exposures_events_Lexis() computes aggregated matrices of exposure times and event counts over two time scales, on the Lexis diagram.

The time scales are t and s. This function uses functions from the package popEpi and from the package Epi, and code shared by Bendix Carstensen on the website bendixcarstensen.com. See also prepare_data() to conveniently prepare individual data for the analysis with one, or two time scales.

Usage

exposures_events_Lexis(t_in = NULL, t_out, s_in = NULL, s_out, ev, bins_list)

Arguments

t_in

(optional) A vector of entry times on the time scale t.

t_out

(optional) A vector of exit times on the time scale t.

s_in

(optional) A vector of entry times on the time scale s.

s_out

A vector of exit times on the time scale s.

ev

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

bins_list

A list with the following (necessary) elements:

  • bins_t a vector of extreme values for the bins over the t axis.

  • nt the number of bins over t.

  • bins_s a vector of extreme values for the bins over the t axis.

  • ns the number of bins over s.

Value

A list with the following elements:

  • R an array of exposure times of dimension \(nt\) by \(ns\)

  • Y an array of event counts of dimension \(nt\) by \(ns\)

References

Carstensen B, Plummer M, Laara E, Hills M (2022). Epi: A Package for Statistical Analysis in Epidemiology. R package version 2.47.1, https://CRAN.R-project.org/package=Epi.

Miettinen J, Rantanen M, Seppa K (2023). popEpi: Functions for Epidemiological Analysis using Population Data. R package version 0.4.11, https://cran.r-project.org/package=popEpi.

Author

Angela Carollo carollo@demogr.mpg.de

Examples

# ---- Bin colon cancer data by time since randomization and time since recurrence ----
# First create vectors of bins (using function `make_bins()`)
bins <- make_bins(t_out = reccolon2ts$timedc, s_out = reccolon2ts$timesr,
dt = 90, ds = 90)
#> `t_in` not provided. I will use `t_in = t_out - s_in`.
#> `s_in = NULL`. I will use `s_in = 0` for all observations.
# Now bin data (note: the t_in and s_in arguments are omitted because data are not left truncated)
bindata2d <- exposures_events_Lexis(t_out = reccolon2ts$timedc,
s_out = reccolon2ts$timesr, ev = reccolon2ts$status, bins = bins)
#> `t_in` not provided. I will use `t_in = t_out - s_in`.
#> `s_in = NULL`. I will use `s_in = 0` for all observations.
#> NOTE: entry.status has been set to 0 for all.