eventWise: Event-wise measures of predictive accuracy

Description Usage Arguments Details

Description

Calculates event-wise sensitivity, specificity, positive and negative predictive value, concordance and net benefit for a vector of predictors.

Usage

1
eventWise(x, y, thresh, weight = NULL, sample = 0)

Arguments

x

Matrix of predicted risks. Each row corresponds to an individual, each column to a trait. Each entry should be a risk between 0 and 1.

y

Matrix of traits. Each row corresponds to an individual, each column to a trait. Must contain binary events coded as 0 and 1.

thresh

Vector of risk thresholds. For each row of x, an event is predicted for each trait that exceeds the corresponding element of thresh. These predictions are then compared to the elements of y.

weight

Weighting matrix. Defaults to identity.

sample

Number of random samples to draw when estimating concordance. Defaults to 0, in which case all pairs of individuals in x are considered.

Details

Event-wise measures consider the prediction of individual events summed over individuals. When weight is the identity matrix, event-wise measures correspond to classical univariate measures with the x matrix vectorised into a column vector. More generally, weight matrices allow different events to contribute more or less to the calculations, and to allow for co-occurence of events within individuals.


DudbridgeLab/multipred documentation built on May 28, 2019, 12:37 p.m.