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Binned Risk Estimates

getBINNEDest.Rd

Calculates bins based on number of evenly spaced bins or n-tiles. Determines average risk within bins, used for risk estimates.

Usage 

getBINNEDest(
  outcome,
  score,
  quantiles = NULL,
  bins = NULL,
  right = TRUE,
  errorbar.sem = NULL
)

Arguments

outcome

Vector of binary outcome for each observation.

score

Numeric vector of continuous predicted risk score.

quantiles

Numeric; quantiles to split bins.

bins

Numeric; number of evenly spaced bins or bin locations.

right

Logical indicating right closed interval. Defaults to TRUE.

errorbar.sem

Scalar numeric representing the number of standard error from the means (SEM) used to calculate risk error bar.

Value

A data frame with 4 columns (score, score percentile, outcome, estimate). Additionally, there is an attribute "errorbar" holding the error-bar data if errorbar.sem was specified.

See also

getASISest() getCGAMest() getGAMest() getMSPLINEest() getPAVAest()

Examples 

# Read in example data
auroc <- read.csv(system.file("extdata", "sample.csv", package = "stats4phc"))
rscore <- auroc$predicted
truth <- as.numeric(auroc$actual)

getBINNEDest(outcome = truth, score = rscore)
#>        score percentile outcome   estimate
#> 1  0.1500925  0.1021021      NA 0.11764706
#> 2  0.1833072  0.2012012      NA 0.09090909
#> 3  0.2034668  0.3003003      NA 0.09090909
#> 4  0.2232864  0.4024024      NA 0.08823529
#> 5  0.2529264  0.5015015      NA 0.24242424
#> 6  0.2759024  0.6006006      NA 0.30303030
#> 7  0.3000654  0.7027027      NA 0.35294118
#> 8  0.3329956  0.8018018      NA 0.54545455
#> 9  0.3679189  0.9009009      NA 0.27272727
#> 10 0.4471575  1.0000000      NA 0.63636364