View source: R/DiscSurvDataTransform.R
dataCensoring | R Documentation |
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.
dataCensoring(dataShort, eventColumns, timeColumn, shortFormat = TRUE)
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(). |
Original data set as argument dataShort, but with added censoring process as first variable in column "yCens".
Thomas Welchowski welchow@imbie.meb.uni-bonn.de
tutzModelDiscdiscSurv
\insertReffahrmeirDiscSurvdiscSurv
\insertRefthompsonTreatmentdiscSurv
contToDisc
,
dataLong
, dataLongTimeDep
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dataLongCompRisks
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)
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