Linked Questions

6
votes
3answers
2k views

Saturated model - why is it perfectly fitted?

I can't understand why is saturated model perfectly fitted? I know the definition, I just don't have any intuition.
5
votes
2answers
2k views

How to construct an interaction plot

I am debating how to construct an interaction plot with my supervisor. We have a dataset comprising 8 independent variables. We are trying to analyse the effect of 2 of the 8 independent variables on ...
8
votes
1answer
1k views

What are the consequences of rare events in logistic regression?

I know that sample size affects power in any statistical method. There are rules are thumb for how many samples a regression needs for each predictor. I also hear often that the number of samples in ...
9
votes
1answer
667 views

Is a saturated model a special case of a overfitted model?

I am trying to make sense of what a saturated model is. AFAIK it's when you have as many features as observations. Can we say a saturated model is a special-case of an extremely overfitted model?
5
votes
1answer
1k views

Is the goodness of fit test in JMP the Hosmer-Lemeshow goodness of fit test?

I'm working with an organization that is using JMP in their analysis, and I can't tell from the description in JMP's help files if the test for goodness of fit in their logistic regression is the ...
0
votes
2answers
2k views
2
votes
2answers
713 views

What do the terms dispersion parameter - deviance - and variance of $y_i$ mean?

I am studying GLMs and I am struggling a bit with some of the concepts. I think mine is more of a theoretical issue. Basically I am a bit confused by the meaning of these three concepts: the variance ...
3
votes
0answers
388 views

Residual deviance for normal distribution with unknown variance?

An older post defines a saturated model as one having as many parameters as observations. I understand how you calculate residual deviance (and its relation to scaled deviance) when the scale is known....
0
votes
0answers
225 views

Why use saturated models as a baseline in GLM model fitting?

From: Interpreting Residual and Null Deviance in GLM R we see that the residual and null deviances are calculated from the baseline log-likelihood value given by the saturated model. It also notes ...
3
votes
1answer
140 views

GLM: Show that in a saturated model, the fitted MLE values $\hat \mu_i = y_i$ for all $i$

Suppose there is a set of $n$ independent observations $y_i$ from the exponential family of distributions. How can we prove that in a saturated GLM model, the fitted MLE values $\hat\mu_i = y_i$ for ...