How to Perform Stepwise Regressions in Stata - Dissertation

Stepwise Regression in Stata Guide for Dissertation | UK, US, Canada Need stepwise forward/backward selection - but supervisor warned theory first? You are in the right place. WHAT YOU WILL LEARN: • stepwise pr(0.05) pe(0.05) logic • Forward vs backward + AIC/BIC compare • How to justify final model for thesis • Common mistakes: pure stepwise atheoretical, p-hacking WHO THIS IS FOR: MSc, PhD Economics, Finance, Business students in UK, US, Canada, Australia, EU. Hi, I'm Dr Bosede Ngozi Adeleye, Senior Lecturer in Economics (University of Lincoln, UK) and Founder of CrunchEconometrix. OFFICIAL LINKS & COMMUNITY: Website: https://cruncheconometrix.com Data Shop: https://cruncheconometrix.com/view/da... Members-Only:    • Members-only videos   Join Membership:    / @cruncheconometrix   Facebook:   / cruncheconometrix   LinkedIn:   / cruncheconometrix   YouTube:    / @cruncheconometrix   GitHub: https://github.com/CrunchEconometrix Twitter: https://x.com/crunchmetrix Teachable (600+ students since 2020, closed 30/9/2026): https://cruncheconometrix.teachable.com Subscribe: https://www.youtube.com/c/CrunchEcono... How to Perform Stepwise Regressions in Stata - Tutorial for MSc Dissertation | UK, US, Canada Are you writing your MSc Economics, Finance, Banking, Management or PhD dissertation and your supervisor asked you to do stepwise regressions in Stata for variable selection - forward selection, backward elimination? You are in the right place. Stepwise regression is a method for selecting variables based on statistical criteria - useful when you have many potential explanatory variables and want parsimonious model. In this complete Stata tutorial, I show you step-by-step how to perform stepwise regressions in Stata. WHAT YOU WILL LEARN: ✓ What is stepwise regression - variable selection method - Forward selection (starts with no variables and adds variables one by one based on p-value entry criteria), Backward elimination (starts with all variables and removes one by one based on p-value removal criteria), Stepwise (both forward and backward - adds and removes) - explained simply for dissertation students ✓ How to do stepwise regression with both forward and backward - stepwise, pr(0.05) pe(0.05): reg Y X1 X2 X3 - adds and removes ✓ Common mistakes MSc students make: Using stepwise without theory - pure data mining - examiners dislike and may deduct marks, Not reporting that stepwise used and criteria pr pe - need to report - e.g., pr(0.05) pe(0.05), Interpreting p-values from stepwise as valid - p-values biased due to selection - need to be cautious and mention limitation, Using stepwise with small sample leading to overfitting - too many variables selected relative to sample size ✓ Alternatives to stepwise regression - theory-driven model (preferred by examiners), Information criteria AIC BIC - compare models via AIC BIC, LASSO regression - modern machine learning variable selection - more robust - but stepwise simpler for MSc WHO THIS IS FOR: MSc, MBA, PhD Economics, Finance, Banking, Management, Business Analytics students in UK (Warwick, Manchester, Leeds, Birmingham, Glasgow, Edinburgh, LSE), US, Canada, Australia, EU with many potential explanatory variables wanting automatic selection. If this helped, LIKE, COMMENT your stepwise variables and country, SHARE. FAQ: Q: What is stepwise regression? A: Variable selection method based on p-value criteria - forward adds, backward removes, stepwise both - automatically selects significant variables - parsimonious model - but theory should guide. Q: How to do stepwise regression in Stata? A: Code: stepwise, pr(0.05) pe(0.05): reg Y X1 X2 X3 - pr = removal if p above 0.05 remove, pe = entry if p below 0.05 enter - final model with significant variables. 0:00 Unlocking the Power of Stepwise Regression 1:07 Preparing Your Data for Stepwise Analysis 1:48 Analyzing Direct Impacts of Regressors 3:21 Testing Consistency Across Multiple Models #StepwiseRegression #Stata #Stepwise #PooledOLS #DummyVariables #VariableSelection #PanelData #StataTutorial #MScDissertation #UKUniversities #Econometrics #BackwardElimination #ForwardSelection #StataPanelData #DissertationHelp #PhDResearch #RegressionAnalysis #ModelSelection #LSDV