Probability-scale residuals for continuous, discrete, and censored data.

ABSTRACT: We describe a new residual for general regression models, defined as pr(Y^* < y) - pr(Y^* > y), where y is the observed outcome and Y^* is a random variable from the fitted distribution. This probability-scale residual can be written as E {sign(y, Y^*)} whereas the popular observed-minus-expected residual can be thought of as E(y - Y^*). Therefore, the probability-scale residual is useful in settings where differences are not meaningful or where the expectation of the fitted distribution cannot be calculated. We present several desirable properties of the probability-scale residual that make it useful for diagnostics and measuring residual corr

SUBMITTER: Shepherd BE 

PROVIDER: S-EPMC5364820 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature