discSurv (version 1.4.1)

contToDisc: Continuous to Discrete Transformation

Description

Discretizes continuous time variable into a specified grid of censored data for discrete survival analysis. It is a data preprocessing step, before the data can be extendend in long format and further analysed with discrete survival models.

Usage

contToDisc(dataSet, timeColumn, intervalLimits, equi=FALSE)

Arguments

dataSet

Original data in short format. Must be of class "data.frame".

timeColumn

Name of the column with discrete survival times. Must be a scalar character value.

intervalLimits

Numeric vector of the right interval borders, e. g. if the intervals are [0, a_1), [a_1, a_2), [a_2, a_max), then intervalLimits = c(a_1, a_2, a_max)

equi

Specifies if argument *intervalLimits* should be interpreted as number of equidistant intervals. Logical only TRUE or FALSE is allowed.

Value

Gives the data set expanded with a first column "timeDisc". This column includes the discrete time intervals (ordered factor).

References

Gerhard Tutz and Matthias Schmid, (2016), Modeling discrete time-to-event data, Springer series in statistics, Doi: 10.1007/978-3-319-28158-2

See Also

dataLong, dataLongTimeDep, dataLongCompRisks

Examples

# NOT RUN {
# Example copenhagen stroke study data
library(pec)
data(cost)
head(cost)

# Convert observed times to months
# Right borders of intervals [0, a_1), [a_1, a_2), ... , [a_{\max-1}, a_{\max})
IntBorders <- 1:ceiling(max(cost$time)/30)*30

# Select subsample
subCost <- cost [1:100, ]
CostMonths <- contToDisc (dataSet=subCost, timeColumn="time", intervalLimits=IntBorders)
head(CostMonths)

# Select subsample giving number of equidistant intervals
CostMonths <- contToDisc (dataSet=subCost, timeColumn="time", intervalLimits=10, equi=TRUE)
head(CostMonths)
# }