Hi my name is Barel, I am looking for some answers about statsmodels.
I want to know if the library has some calculations and how to implement them with the library. I am working in the lab for metabolism. my data is on calorimetry experiments.
All the calculation approach explained in this article:
I need it because my design experiment differs than does the app and I know python. I work with the library a bit but got stuck on a couple of things. Hope someone could explain and direct me:
1. the glm() is the same as the article provided, it doesn't have the F ratio or the same values when I am doing the calculation on the data that I have the answer to.
2. there are post hoc functions in statmodles. but I saw there isn't the implementation of dunnett test just the tukyHSD. There will be soon this implementation?
3. about the glm() or other function that will help me implement the same calculation as the calr providing could you just show me one example or direct to the right place so will be sure where to look?
Based on a very quick look at the Cell Metabolism article
If the model is Gaussian with identity link, then it is better to use OLS, and then use `anova_lm` for the test of effects.
For GLM there are no premade hypotheses tests, so it depends on the user to specify the contrast matrix for the relevant hypotheses.
To replicate with GLM for other models, we would need more information about the design matrix and how the hypothesis/contrast matrix is defined.
dunnet's test for multiple comparison to a reference category is not available. The main limitation is to get the p-values or critical values. The contrast matrix itself is easy to build for a specific case.
- use generic multiple testing p-value corrections
- use multivariate t-distribution directly to compute p-values, I only ever tried to replicate tukeyHSD, but not Dunnet
or use a table with critical values from the literature