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dataCensoring

Data Censoring Transformation


Description

Function for transformation of discrete survival times in censoring encoding. Prior this function the data has to be already transformed to long format. With this new generated variable, the discrete censoring process can be analysed 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(dataSetLong, respColumn, timeColumn)

Arguments

dataSetLong

Original data in transformed long format.

respColumn

Name of column of discrete survival response (character scalar).

timeColumn

Name of column of discrete time intervals (character scalar).

Details

The standard procedure is to use functions such as dataLong, dataLongTimeDep, dataLongCompRisks to augment the data set from short format to long format before using dataCensoring.

Value

Original data set as argument *dataSetLong*, but with added censoring process as first variable in column "yCens"

Author(s)

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

Ludwig Fahrmeir, (1997), Discrete failure time models, LMU Sonderforschungsbereich 386, Paper 91, http://epub.ub.uni-muenchen.de/

W. A. Thompson Jr., (1977), On the Treatment of Grouped Observations in Life Studies, Biometrics, Vol. 33, No. 3

See Also

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 (dataSet=subCost, timeColumn="time", intervalLimits=IntBorders)
head(CostMonths)

# Convert to long format based on months
CostMonthsLong <- dataLong (dataSet=CostMonths, timeColumn="timeDisc", censColumn="status")
head(CostMonthsLong, 20)

# Generate censoring process variable
CostMonthsCensor <- dataCensoring (dataSetLong=CostMonthsLong, 
respColumn="y", timeColumn="timeInt")
head(CostMonthsCensor)
tail(CostMonthsCensor [CostMonthsCensor$obj==1, ], 10)
tail(CostMonthsCensor [CostMonthsCensor$obj==3, ], 10)

discSurv

Discrete Time Survival Analysis

v1.4.1
GPL-3
Authors
Thomas Welchowski <welchow@imbie.meb.uni-bonn.de> and Matthias Schmid <matthias.schmid@imbie.uni-bonn.de>
Initial release
2019-12-10

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