Converts objects to MCC class. This is useful when you have calculation results from other sources that you want to treat as MCC objects.
Examples
# Convert a data.frame to MCC object
library(dplyr)
# Create a simple data.frame with MCC results
mcc_data <- data.frame(
time = c(1, 2, 3, 4, 5),
mcc = c(0.1, 0.3, 0.5, 0.7, 1.0)
)
# Convert to MCC object (equation method)
mcc_obj <- as_mcc(mcc_data, method = "equation")
print(mcc_obj)
#>
#> ── Mean Cumulative Count Results ───────────────────────────────────────────────
#> ℹ Method: Dong-Yasui Equation Method
#>
#> ── MCC Estimates ──
#>
#> # A tibble: 5 × 2
#> time mcc
#> <dbl> <dbl>
#> 1 1 0.1
#> 2 2 0.3
#> 3 3 0.5
#> 4 4 0.7
#> 5 5 1
is_mcc(mcc_obj) # TRUE
#> [1] TRUE
# Convert for SCI method (requires SumCIs column)
sci_data <- data.frame(
time = c(1, 2, 3, 4, 5),
SumCIs = c(0.1, 0.3, 0.5, 0.7, 1.0)
)
mcc_sci_obj <- as_mcc(sci_data, method = "sci")
print(mcc_sci_obj)
#> ── Mean Cumulative Count Results ───────────────────────────────────────────────
#> ℹ Method: Sum of Cumulative Incidence Method
#>
#> ── MCC Estimates ──
#>
#> # A tibble: 5 × 2
#> time SumCIs
#> <dbl> <dbl>
#> 1 1 0.1
#> 2 2 0.3
#> 3 3 0.5
#> 4 4 0.7
#> 5 5 1
# Convert a list to MCC object
mcc_list <- list(
mcc_final = data.frame(
time = c(1, 2, 3),
mcc = c(0.2, 0.5, 0.8)
)
)
mcc_from_list <- as_mcc(mcc_list, method = "equation")
print(mcc_from_list)
#> ── Mean Cumulative Count Results ───────────────────────────────────────────────
#> ℹ Method: Dong-Yasui Equation Method
#>
#> ── MCC Estimates ──
#>
#> time mcc
#> 1 1 0.2
#> 2 2 0.5
#> 3 3 0.8
# Clean up
rm(mcc_data, sci_data, mcc_list, mcc_obj, mcc_sci_obj, mcc_from_list)