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What does AIC stand for in logistic regression?
AIC is an estimate of the information lost when a given model is used to represent the process that generates the data. L be the maximum value of the likelihood function for the model. k is the number of independent variables.
Why is the AIC of a log likelihood model lower?
We have two models that use the same method to calculate log likelihood and the AIC for one is lower than the other. However, the one with the lower AIC is far more difficult to interpret. We are having trouble deciding if it is worth introducing the difficulty and we judged this using a percentage difference in AIC.
When to use AIC or BIC for model comparison?
I think AICc can be used to compare models based on different sample sizes. My rule of thumb is to use BIC instead of AIC when sample sizes are different. AIC is still admissible, the log likelihood input indirectly accounts for different sample sizes.
How to compare AIC based on different sample sizes?
There is AICc, which is AIC with a correction for sample size: AICc = AIC + 2k (k + 1)/ (n – k – 1) where ”n” denotes the sample size and ”k” denotes the number of parameters. I think AICc can be used to compare models based on different sample sizes.
Which is lower null or full model AIC?
I have run a model similar to this on a completely separate data set which returned AIC values for the full model significantly lower than the null: null AIC was over 1000, full model AIC was just over 300. I would have expected similar behavior for the second data set (given that it is very similar data) and I am unsure what to make of the output.
How to create null model for conditional logistic regression in R?
How to create a null model for conditional logistic regression in R? I would like to see if including some covariates will give me an AIC which is smaller than the null model, while working with conditional logistic regression in R (discrete choice). But I am a little unsure as to how I can create a null model to compare this against.
How to create a null model for R?
– Stack Overflow How to create a null model for conditional logistic regression in R? I would like to see if including some covariates will give me an AIC which is smaller than the null model, while working with conditional logistic regression in R (discrete choice).