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How to be confident in your regression results

Learn the key techniques and principles to be confident in your regression results. Discover the 5 weird regression tricks that editors don't want you to know about. This workshop by Brigham R. Frandsen Family Studies Center will also cover the social scientific process, data analysis, estimation, and statistical inference.

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How to be confident in your regression results

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  1. How to be confident in your regression results Brigham R. Frandsen Family Studies Center Methods Workshop November 6, 2015

  2. 5 Weird Regression Tricks Editors Don’t Want You to Know About Brigham R. Frandsen Family Studies Center Methods Workshop November 6, 2015

  3. The Social Scientific Process

  4. 6-Million Dollar Question

  5. Design • Causal • Experimenter-controlled randomized experiment • Natural experiment • Differences-in-differences • Selection-on-observables • Descriptive • What is the population of interest? • Does the relationship of interest live at the individual (micro) level, or aggregate (macro) level?

  6. Model • Translate your English to math • Start simple

  7. Data • Match data to design • Look at your data • Histograms • Scatter plots • Summary statistics • Tabulations • Find the bugaboos • Censoring • Sample selection • Missing data • Clustered sampling

  8. Estimation • Trade efficiency for robustness • Understand assumptions and consequences • Example: omitted variables bias • Test what’s falsifiable • Check robustness to modeling and data choices • Probe sensitivity to outliers • Compare median regression to mean regression • Look at residual histogram

  9. Inference • Don’t trust what Stata or R spits out by default • Rules of thumb for variance formula: • Cross-sectional data, micro variation: use the Huber-Eicker-White heteroscedasticity-robust formula • Cross-sectional data, aggregate variation: use the cluster variance formula • Panel (longitudinal) data: cluster at the individual level • Time series data: Newey-West variance formula • Quit star-gazing!

  10. Wrap up • Ask a coherent question! • Make sure design is equipped to answer it! • Match data to design! • Choose transparency and robustness over efficiency and sophistication! • Be skeptical of defaults and don’t star gaze!

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