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logis.fit: Graphical adujstment of a simple binary logistic regression to data

Description

Cut the data into intervals, compute the response probability and its standard error for each interval and add the results to the regression curve. No test is performed but this permits to have a graphical idea of the adjustment of the model to the data.

Usage

logis.fit(model, int = 5, ...)

Arguments

model
glm model.
int
number of intervals.
...
other arguments. See help of points and segments.

See Also

glm

Examples

Run this code
x <- 1:50
y <- c(rep(0,18),sample(0:1,14,replace=TRUE),rep(1,18))
model <- glm(y~x,family=binomial)
plot(x,y)
lines(x,model$fitted)
logis.fit(model)

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