Multiple regression

What it means

Multiple regression estimates how an outcome is associated with several predictors while holding the other included predictors constant.

How to do it

1. Define the question

Name the outcome, predictors, population and period. Explain why each variable belongs in the model.

2. Check the data and model

Inspect missing values, unusual observations, functional form, residuals and predictor overlap before interpreting coefficients.

3. Interpret in context

Report direction, size, units and uncertainty. Keep the interpretation conditional on the other included predictors.

Common mistakes & limitations

Association is not causation

A fitted coefficient does not by itself prove a causal effect. Omitted variables, measurement choices and model assumptions can change the result.

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