adjDevResid: 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)

References

tutzModelDiscdiscSurv tutzRegCatdiscSurv

Examples

Run this code

# NOT RUN {
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

# }