adjDevResid: Adjusted Deviance Residuals in short format

In discSurv: Discrete Time Survival Analysis

Adjusted Deviance Residuals in short format

Description

Calculates the adjusted deviance residuals for arbitrary prediction models. The adjusted deviance residuals should be approximately normal distributed, in the case of a well fitting model.

Usage

adjDevResid(dataLong, hazards)

Arguments

dataLong	Data set in long format ("class data.frame").
hazards	Estimated discrete hazards of the data in long format("numeric vector"). Hazard rates are probabilities and therefore restricted to the interval [0, 1].

Value

• Output List with objects:

  • AdjDevResid Adjusted deviance residuals as numeric vector

• Input A list of given argument input values (saved for reference)

Author(s)

Thomas Welchowski [e-mail]

References

\insertRef

tutzModelDiscdiscSurv

\insertReftutzRegCatdiscSurv

See Also

intPredErr, predErrCurve

Examples

library(survival)

# Transform data to long format
heart[, "stop"] <- ceiling(heart[, "stop"])
set.seed(0)
Indizes <- sample(unique(heart$id), 25)
randSample <- heart[unlist(sapply(1:length(Indizes), 
function(x) which(heart$id == Indizes[x]))),]
heartLong <- dataLongTimeDep(dataSemiLong = randSample, 
timeColumn = "stop", eventColumn = "event", idColumn = "id", timeAsFactor = FALSE)

# Fit a generalized, additive model and predict discrete hazards on data in long format
library(mgcv)
gamFit <- gam(y ~ timeInt + surgery + transplant + s(age), data = heartLong, family = "binomial")
hazPreds <- predict(gamFit, type = "response")

# Calculate adjusted deviance residuals
devResiduals <- adjDevResid(dataLong = heartLong, hazards = hazPreds)$Output$AdjDevResid
devResiduals

discSurv documentation built on March 18, 2022, 7:12 p.m.