Tagged Questions

2
votes
1answer
72 views

What is the dimension (k) of these regression models?

I am attempting to use Akaike's Information Criterion to select the most appropriate model for some data. This means I need to find the likelihood of my data under various models, compute the AIC ...
0
votes
0answers
63 views

How do I explain that software implemented model selection procedures should not be used unsupervised?

I know that people generally say that procedures which select a model based on information criterion lead to inconsistent model selections. I read a paper by Leeb and Potscher (2005), MODEL SELECTION ...
3
votes
2answers
269 views

Prerequisites for AIC model comparison

What are exactly the prerequisites, that need to be fulfilled for AIC model comparison to work? I just came around this question when I did comparison like this: ...
0
votes
0answers
57 views

AIC with multiple linear slopes

I have a set of data points. I would like to know which model of linear slopes best fits the data: two slopes, three slopes, or four slopes. How can I calculate the AIC for each of these models (i.e, ...
8
votes
1answer
362 views

What is the difference between AIC() and extractAIC() in R?

The R documentation for either does not shed much light. All that I can get from this link is that using either one should be fine. What I do not get is why they are not equal. Fact: The stepwise ...
5
votes
2answers
297 views

Why does log likelihood function for a model use SSE/n and not SSE/df?

I'm trying to find out how log-likelihood function works for linear regression. I found the formula here and here. Making some experiments with it (see code below), I was quite surprised that the ...
0
votes
2answers
135 views

Selecting the best indicator of disease progression

Quite a while ago, I asked a question for which Peter Ellis provided a very interesting answer. Now I'd like to follow on that and have your comments and ideas on how to actually put it to use. I try ...
20
votes
8answers
4k views

Do all interactions terms need their individual terms in regression model?

I am actually reviewing a manuscript where the authors compare 5-6 logit regression models with AIC. However, some of the models have interaction terms without including the individual covariate ...
4
votes
1answer
448 views

Will AIC and R-square rank models similarly if the number of variables is equal?

This is a fairly basic question: If a number of regression models are being evaluated for fit to a dataset, and each model has 3 variables, will AIC and R-square rank the models similarly? I'm ...
3
votes
2answers
449 views

Which measure of model fit to report when performing likelihood based regression: AIC, BIC, Pseudo R-square?

I'd like to hear your opinions on the following: What parameters would you report when estimating different likelihood based regression? AIC, BIC, Pseudo $R^2$? What is the standard to report? ...
7
votes
2answers
2k views

Testing the difference in AIC of two non-nested models

The whole point of AIC or any other information criterion is that less is better. So if I have two models M1: y = a0 + XA + e and M2: y = b0 + ZB + u, and if the AIC of the first (A1) is less than ...
3
votes
1answer
558 views

Question on AIC and stepAIC

AIC(lm(Fertility ~ ., data=swiss)) [1] 326.0716 ok, since AIC is calculated as ...
8
votes
2answers
787 views

Comparing regression models

I recently fit 4 multiple regression models for the same predictor/response data. Two of the models I fit with Poisson regression. ...
-1
votes
1answer
236 views

Shall I trust AIC (non-full model) or slope (full model)?

The purpose to run regressions for butterfly richness again 5 environmental variables is to show the importance rank of the independent variables mainly by AIC. In non-full models, they reveal that ...