Model Comparison
Models can be compared to each other. This can either be done when you have done an exploratory data analysis or a confirmatory data analysis. In an exploratory analysis, you formulate all models you can think of, and see which describes your data best. In a confirmatory analysis you test which of your models you have described before the data was collected fits the data best, or test if your only model fits the data. In linear regression analysis you can compare the amount of variance explained by the independent variables, R2, across the different models. In general, you can compare models that are nested by using a Likelihood-ratio test. Nested models are models that can be obtained by restricting a parameter in a more complex model to be zero.
Read more about this topic: Statistical Models
Famous quotes containing the words model and/or comparison:
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—Oscar Wilde (1854–1900)
“The difference between human vision and the image perceived by the faceted eye of an insect may be compared with the difference between a half-tone block made with the very finest screen and the corresponding picture as represented by the very coarse screening used in common newspaper pictorial reproduction. The same comparison holds good between the way Gogol saw things and the way average readers and average writers see things.”
—Vladimir Nabokov (1899–1977)