Extracts the MCC estimates from an mcc object and returns them as a
standard data.frame. This is useful for further analysis or when working
with packages that expect standard data.frame objects.
Usage
# S3 method for class 'mcc'
as.data.frame(x, ...)Examples
# Create sample data
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
df <- data.frame(
id = c(1, 2, 3, 4, 4, 4, 5, 5),
time = c(8, 1, 5, 2, 6, 7, 3, 3),
cause = c(0, 0, 2, 1, 1, 1, 1, 2)
) |>
arrange(id, time)
# Calculate MCC
mcc_result <- mcc(df, "id", "time", "cause")
#> Warning: Found 1 participant where last observation is an event of interest (`cause_var`
#> = 1)
#> ! ID: 4
#> ℹ `mcc()` assumes these participants are censored at their final `time_var`
#> ℹ If participants were actually censored or experienced competing risks after
#> their last event, add those observations to ensure correct estimates
#> ℹ Adjusted time points for events occurring simultaneously for the same subject.
# Convert to data.frame
mcc_df <- as.data.frame(mcc_result)
print(mcc_df)
#> time mcc
#> 1 0 0.00
#> 2 2 0.25
#> 3 3 0.50
#> 4 6 0.75
#> 5 7 1.00
class(mcc_df) # "data.frame"
#> [1] "data.frame"
# This is equivalent to extracting mcc_final
identical(mcc_df, as.data.frame(mcc_result$mcc_final))
#> [1] TRUE
# Useful for further analysis with base R functions
summary(mcc_df)
#> time mcc
#> Min. :0.0 Min. :0.00
#> 1st Qu.:2.0 1st Qu.:0.25
#> Median :3.0 Median :0.50
#> Mean :3.6 Mean :0.50
#> 3rd Qu.:6.0 3rd Qu.:0.75
#> Max. :7.0 Max. :1.00
plot(mcc_df$time, mcc_df$mcc, type = "s")
# Clean up
rm(df, mcc_result, mcc_df)