R/quantile.prodlim.R
quantile.prodlim.RdQuantiles for Kaplan-Meier and Aalen-Johansen estimates.
# S3 method for class 'prodlim'
quantile(x, q, cause = 1, ...)library(lava)
set.seed(1)
d=SimSurv(30)
# Quantiles of the potential followup time
g=prodlim(Hist(time,status)~1,data=d,reverse=TRUE)
quantile(g)
#> Quantiles of the potential follow up time distribution based on the Kaplan-Meier method
#> applied to the censored times reversing the roles of event status and censored.
#>
#> Table of quantiles and corresponding confidence limits:
#> q quantile lower upper
#> <num> <num> <num> <num>
#> 1: 0.00 NA NA NA
#> 2: 0.25 NA 9.17 NA
#> 3: 0.50 9.17 5.79 NA
#> 4: 0.75 5.79 4.58 9.2
#> 5: 1.00 0.86 0.86 4.6
#>
#>
#> Median with interquartile range (IQR):
#> Median (IQR)
#> <char>
#> 1: 9.17 (5.79;NA)
# survival time
f=prodlim(Hist(time,status)~1,data=d)
f1=prodlim(Hist(time,status)~X1,data=d)
# default: median and IQR
quantile(f)
#> Quantiles of the event time distribution based on the Kaplan-Meier method.
#>
#> Table of quantiles and corresponding confidence limits:
#> q quantile lower upper
#> <num> <num> <num> <num>
#> 1: 0.00 NA NA NA
#> 2: 0.25 11.28 6.42 NA
#> 3: 0.50 5.26 4.45 9.2
#> 4: 0.75 3.49 2.50 5.0
#> 5: 1.00 0.49 0.49 2.5
#>
#>
#> Median with interquartile range (IQR):
#> Median (IQR)
#> <char>
#> 1: 5.26 (3.49;11.28)
quantile(f1)
#> Quantiles of the event time distribution based on the Kaplan-Meier method.
#>
#> Table of quantiles and corresponding confidence limits:
#> X1 q quantile lower upper
#> <num> <num> <num> <num> <num>
#> 1: 0 0.00 NA NA NA
#> 2: 0 0.25 11.28 9.16 NA
#> 3: 0 0.50 9.16 6.42 NA
#> 4: 0 0.75 5.00 3.10 9.2
#> 5: 0 1.00 1.55 1.55 5.0
#> 6: 1 0.00 NA NA NA
#> 7: 1 0.25 5.26 3.71 NA
#> 8: 1 0.50 4.45 2.73 5.1
#> 9: 1 0.75 2.73 0.75 4.4
#> 10: 1 1.00 0.49 0.49 2.5
#>
#>
#> Median with interquartile range (IQR):
#> X1 Median (IQR)
#> <num> <char>
#> 1: 0 9.16 (5.00;11.28)
#> 2: 1 4.45 (2.73;5.26)
# median alone
quantile(f,.5)
#> Quantiles of the event time distribution based on the Kaplan-Meier method.
#>
#> Table of quantiles and corresponding confidence limits:
#> q quantile lower upper
#> <num> <num> <num> <num>
#> 1: 0.5 5.3 4.4 9.2
quantile(f1,.5)
#> Quantiles of the event time distribution based on the Kaplan-Meier method.
#>
#> Table of quantiles and corresponding confidence limits:
#> X1 q quantile lower upper
#> <num> <num> <num> <num> <num>
#> 1: 0 0.5 9.2 6.4 NA
#> 2: 1 0.5 4.4 2.7 5.1
# competing risks
set.seed(3)
dd = SimCompRisk(30)
ff=prodlim(Hist(time,event)~1,data=dd)
ff1=prodlim(Hist(time,event)~X1,data=dd)
## default: median and IQR
quantile(ff)
#> Quantiles of the event time distribution based on the Aalen-Johansen method.
#>
#> Table of quantiles and corresponding confidence limits:
#> cause q quantile lower upper
#> <char> <num> <num> <num> <num>
#> 1: 1 0.00 1.6 1.6 1.9
#> 2: 1 0.25 3.6 1.9 5.5
#> 3: 1 0.50 8.1 4.3 NA
#> 4: 1 0.75 NA 8.7 NA
#> 5: 1 1.00 NA NA NA
#>
#>
#> Median with interquartile range (IQR):
#> cause Median (IQR)
#> <char> <char>
#> 1: 1 8.07 (3.61;NA)
quantile(ff1)
#> Quantiles of the event time distribution based on the Aalen-Johansen method.
#>
#> Table of quantiles and corresponding confidence limits:
#> cause X1 q quantile lower upper
#> <char> <num> <num> <num> <num> <num>
#> 1: 1 0 0.00 3.0 3.0 5.5
#> 2: 1 0 0.25 5.5 3.0 NA
#> 3: 1 0 0.50 NA 5.5 NA
#> 4: 1 0 0.75 NA NA NA
#> 5: 1 0 1.00 NA NA NA
#> 6: 1 1 0.00 1.6 1.6 1.9
#> 7: 1 1 0.25 3.0 1.8 5.0
#> 8: 1 1 0.50 5.2 3.6 8.7
#> 9: 1 1 0.75 8.7 5.2 NA
#> 10: 1 1 1.00 NA NA NA
#>
#>
#> Median with interquartile range (IQR):
#> cause X1 Median (IQR)
#> <char> <num> <char>
#> 1: 1 0 NA (5.51;NA)
#> 2: 1 1 5.20 (2.98;8.74)
print(quantile(ff1),na.val="NA")
#> Quantiles of the event time distribution based on the Aalen-Johansen method.
#>
#> Table of quantiles and corresponding confidence limits:
#> cause X1 q quantile lower upper
#> <char> <num> <num> <num> <num> <num>
#> 1: 1 0 0.00 3.0 3.0 5.5
#> 2: 1 0 0.25 5.5 3.0 NA
#> 3: 1 0 0.50 NA 5.5 NA
#> 4: 1 0 0.75 NA NA NA
#> 5: 1 0 1.00 NA NA NA
#> 6: 1 1 0.00 1.6 1.6 1.9
#> 7: 1 1 0.25 3.0 1.8 5.0
#> 8: 1 1 0.50 5.2 3.6 8.7
#> 9: 1 1 0.75 8.7 5.2 NA
#> 10: 1 1 1.00 NA NA NA
#>
#>
#> Median with interquartile range (IQR):
#> cause X1 Median (IQR)
#> <char> <num> <char>
#> 1: 1 0 NA (5.51;NA)
#> 2: 1 1 5.20 (2.98;8.74)
print(quantile(ff1),na.val="Not reached")
#> Quantiles of the event time distribution based on the Aalen-Johansen method.
#>
#> Table of quantiles and corresponding confidence limits:
#> cause X1 q quantile lower upper
#> <char> <num> <num> <num> <num> <num>
#> 1: 1 0 0.00 3.0 3.0 5.5
#> 2: 1 0 0.25 5.5 3.0 NA
#> 3: 1 0 0.50 NA 5.5 NA
#> 4: 1 0 0.75 NA NA NA
#> 5: 1 0 1.00 NA NA NA
#> 6: 1 1 0.00 1.6 1.6 1.9
#> 7: 1 1 0.25 3.0 1.8 5.0
#> 8: 1 1 0.50 5.2 3.6 8.7
#> 9: 1 1 0.75 8.7 5.2 NA
#> 10: 1 1 1.00 NA NA NA
#>
#>
#> Median with interquartile range (IQR):
#> cause X1 Median (IQR)
#> <char> <num> <char>
#> 1: 1 0 NA (5.51;NA)
#> 2: 1 1 5.20 (2.98;8.74)