Compute Residuals for survreg Objects

DESCRIPTION:

Note: The survreg function is deprecated; please use instead. Compute deviance, Pearson, working or matrix residuals for a parametric survival model. This is a method for the function residuals for objects inheriting from class survreg. However, as several types of residuals are available for survreg objects, there is an additional optional argument type.

USAGE:

residuals.survreg(object, type="deviance")

REQUIRED ARGUMENTS:

object
an object inheriting from class survreg, representing a parametric survival model. Typically this is the output from the survreg function.

OPTIONAL ARGUMENTS:

type
type of residuals, with choices "deviance", "pearson", "working" or "matrix".

VALUE:

a vector of residuals is returned.

The sum of squared deviance residuals add up to the deviance. The Pearson residuals are standardized residuals on the scale of the response. The working residuals reside on the object, and are the residuals from the final IRLS fit.

The matrix type produces a matrix based on derivatives of the log-likelihood function. Let L be the log-likelihood, p be the linear predictor X %*% coef, and s be log(sigma). Then the 6 columns of the matrix are L, dL/dp, ddL/(dp dp), dL/ds, ddL/(ds ds) and ddL/(dp ds), where d stands for the derivative and dd the second derivative. Diagnostics based on these quantities are discussed in Escobar and Meeker (1992).

REFERENCES:

Escobar, L. A. and Meeker, W. Q. (1992). Assessing influence in regression analysis with censored data. Biometrics 48, 507-528.

SEE ALSO:

,

EXAMPLES:

fit <- survreg(Surv(days, event) ~ voltage, data=capacitor)
rr <- residuals(fit, type="matrix")