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.
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