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Logit coefficients don't answer real questions. Stata's margins command turns them into adjusted predictions and average marginal effects — here's how to use it, and where it can mislead.
Step‑by‑step guide to fit a logistic model in Stata, compute average marginal effects with margins, save them to a dataset, and export to Excel.
I have a dataset consisting of both numeric and categorical data and I want to predict adverse outcomes for patients based on their medical characteristics. I defined a prediction pipeline for my dataset like so: X = dataset.drop(columns=['target']) y = dataset['target'] # define categorical and numeric transformers numeric_transformer = Pipeline(steps=[ ('k
stata
python