Checking model fit
In the video you analyzed the example of an improvement in the model fit by adding additional variable on the wells
data. Continuing with this data set you will see how further increase in model complexity effects deviance and model fit.
The dataset wells
have been preloaded in the workspace.
Este exercício faz parte do curso
Generalized Linear Models in Python
Instruções do exercício
- Fit a logistic regression model with
switch
as the response anddistance100
andarsenic
as explanatory variables. - Compute the difference in deviance of the intercept only model and the model including all the variables.
- Print the computed difference.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Import statsmodels
import ____.____ as sm
from ____.____.____ import glm
# Define model formula
formula = '____ ~ ____'
# Fit GLM
model_dist_ars = glm(____, ____ = ____, ____ = sm.____.____).____
# Compare deviance of null and residual model
diff_deviance = ____.____ - ____.____
# Print the computed difference in deviance
____(____)