| dataCensoring {discSurv} | R Documentation |
Data Censoring Transformation for short formats
Description
Function for transformation of discrete survival times in censoring encoding. The original data is expanded to include the censoring process. Alternatively the long data format can also be augmented. With the new generated variable "yCens", the discrete censoring process can be analyzed instead of the discrete survival process. In discrete survival analysis this information is used to constructs weights for predictive evaluation measures. It is applicable in single event survival analysis.
Usage
dataCensoring(dataShort, eventColumns, timeColumn, shortFormat = TRUE)
Arguments
dataShort |
Original data set in short format ("class data.frame"). |
eventColumns |
Name of event columns ("character vector"). The event columns have to be in binary format. If the sum of all events equals zero in a row, then this observation is interpreted as censored. |
timeColumn |
Name of column with discrete time intervals ("character vector"). |
shortFormat |
Is the supplied data set dataShort not preprocessed with function dataLong() ("logical vector")? Default is TRUE. If shortFormat=FALSE then it is assumed that the data set was augmented with function dataLong(). |
Value
Original data set as argument dataShort, but with added censoring process as first variable in column "yCens".
Author(s)
Thomas Welchowski welchow@imbie.meb.uni-bonn.de
References
Tutz G, Schmid M (2016).
Modeling discrete time-to-event data.
Springer Series in Statistics.
Fahrmeir L (2005).
“Discrete Survival-Time Models.”
In Encyclopedia of Biostatistics, chapter Survival Analysis.
John Wiley \& Sons.
Thompson Jr. WA (1977).
“On the Treatment of Grouped Observations in Life Studies.”
Biometrics, 33, 463-470.
See Also
contToDisc,
dataLong, dataLongTimeDep,
dataLongCompRisks
Examples
library(pec)
data(cost)
head(cost)
IntBorders <- 1:ceiling(max(cost$time)/30)*30
subCost <- cost [1:100, ]
# Convert from days to months
CostMonths <- contToDisc(dataShort=subCost, timeColumn="time", intervalLimits=IntBorders)
head(CostMonths)
# Generate censoring process variable in short format
CostMonthsCensorShort <- dataCensoring (dataShort = CostMonths,
eventColumns = "status", timeColumn = "time", shortFormat = TRUE)
head(CostMonthsCensorShort)
################################
# Example with long data format
library(pec)
data(cost)
head(cost)
IntBorders <- 1:ceiling(max(cost$time)/30)*30
subCost <- cost [1:100, ]
# Convert from days to months
CostMonths <- contToDisc(dataShort = subCost, timeColumn = "time", intervalLimits = IntBorders)
head(CostMonths)
# Convert to long format based on months
CostMonthsLong <- dataLong(dataShort = CostMonths, timeColumn = "timeDisc", eventColumn = "status")
head(CostMonthsLong, 20)
# Generate censoring process variable
CostMonthsCensor <- dataCensoring (dataShort = CostMonthsLong, timeColumn = "timeInt",
shortFormat = FALSE)
head(CostMonthsCensor)
tail(CostMonthsCensor [CostMonthsCensor$obj==1, ], 10)
tail(CostMonthsCensor [CostMonthsCensor$obj==3, ], 10)