While comparing the protein oligomerization between different samples say A and B, sample A data fits one model and sample B data fits another model. Here, we are interested in understanding the behavior of the common component present in A and B statistically.
What methods can be applied to afford the statistical significance between fitting models for A and B ?
I have protein oligomerization data grouped according to different construct combinations. Three sample sets have co-expression of two proteins and one has single expression of protein.
The single expression of protein data set fits with a sigmoidal function while the other datasets are fitted to a non-linear function.
And I require to compare these different data sets to make a comparison of protein oligomerization between these different construct combinations for my work.
Hope this description helps
Since you have two models with different variables you can't compare them directly..if your two models contain the same variables then they can be compared by using statistics like AIC and BIC. See. The attached for an example. Best wishes David Booth
Thank you David for that recommendation. I will check into AIC and BIC statistics
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