breakDown (version 0.2.2)

broken.glm: Breaking Down of Model Predictions for glm models

Description

Breaking Down of Model Predictions for glm models

Usage

# S3 method for glm
broken(
  model,
  new_observation,
  ...,
  baseline = 0,
  predict.function = stats::predict.glm
)

Value

an object of the broken class

Arguments

model

a glm model

new_observation

a new observation with columns that corresponds to variables used in the model

...

other parameters

baseline

the origin/baseline for the breakDown plots, where the rectangles start. It may be a number or a character "Intercept". In the latter case the orgin will be set to model intercept.

predict.function

function that will calculate predictions out of model (typically predict or betas)

Examples

# example for wine data
wine$qualityb <- factor(wine$quality > 5.5, labels = c("bad", "good"))
modelg <- glm(qualityb~fixed.acidity + volatile.acidity + citric.acid +
              residual.sugar + chlorides + free.sulfur.dioxide +
              total.sulfur.dioxide + density + pH + sulphates + alcohol,
    data=wine, family = "binomial")
new_observation <- wine[1,]
br <- broken(modelg, new_observation)
logit <- function(x) exp(x)/(1+exp(x))
plot(br, logit)

# example for HR_data
model <- glm(left~., data = HR_data, family = "binomial")
explain_1 <- broken(model, HR_data[1,])
explain_1
plot(explain_1)
plot(explain_1, trans = function(x) exp(x)/(1+exp(x)))

explain_2 <- broken(model, HR_data[1,], predict.function = betas)
explain_2
plot(explain_2, trans = function(x) exp(x)/(1+exp(x)))