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Regression Pillar

OLS, robust and clustered inference, nonlinear models, and postestimation.

20 guides in this category

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Step 1

regress in Stata: OLS Basics and Correct Interpretation

Run regress stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 2

Robust Standard Errors in Stata: vce(robust) and Interpretation

Run robust standard errors stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 3

Clustered Standard Errors in Stata: vce(cluster) Do and Don't

Run cluster standard errors stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 4

Multicollinearity in Stata: VIF, Dropped Variables, and Redesign

Run multicollinearity stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 5

margins in Stata: Predictions, AMEs, and Clean Interpretation

Run margins stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 6

Factor Variables in Stata: i., c., Interactions, and Base Levels

Run i. factor variables stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 7

Interaction Terms in Stata: c.x##i.group with margins

Run interaction term stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

Step 8

Fixed Effects in Stata with xtreg, fe: Assumptions and Output

Run xtreg fe stata in Stata with coefficient interpretation, inference checks, and practical modeling decisions for real datasets.

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