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Chapter 9

Chapter 9. Assessing Studies Based on Multiple Regression. Assessing Studies Based on Multiple Regression (SW Chapter 9). Is there a systematic way to assess regression studies?. A Framework for Assessing Statistical Studies: Internal and External Validity (SW Section 9.1).

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Chapter 9

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  1. Chapter 9 Assessing Studies Based on Multiple Regression

  2. Assessing Studies Based on Multiple Regression (SW Chapter 9)

  3. Is there a systematic way to assess regression studies?

  4. A Framework for Assessing Statistical Studies: Internal and External Validity (SW Section 9.1)

  5. Threats to External Validity of Multiple Regression Studies

  6. Threats to Internal Validity of Multiple Regression Analysis (SW Section 9.2)

  7. 1. Omitted variable bias

  8. Potential solutions to omitted variable bias

  9. 2. Wrong functional form

  10. 3. Errors-in-variables bias

  11. In general, measurement error in a regressor results in “errors-in-variables” bias.

  12. “Errors-in-variables” bias, ctd.

  13. Potential solutions to errors-in-variables bias

  14. 4. Sample selection bias

  15. Example #1: Mutual funds

  16. Sample selection bias induces correlation between a regressor and the error term.

  17. Example #2: returns to education

  18. Potential solutions to sample selection bias

  19. 5. Simultaneous causality bias

  20. Simultaneous causality bias in equations

  21. Potential solutions to simultaneous causality bias

  22. Internal and External Validity When the Regression is Used for Forecasting (SW Section 9.3)

  23. Applying External and Internal Validity: Test Scores and Class Size(SW Section 9.4)

  24. Check of external validity

  25. The Massachusetts data: summary statistics

  26. Predicted effects for a class size reduction of 2

  27. Summary of Findings for Massachusetts

  28. Comparison of estimated class size effects: CA vs. MA

  29. Summary: Comparison of California and Massachusetts Regression Analyses

  30. Step back: what are the remaining threats to internal validity in the test score/class size example?

  31. Omitted variable bias, ctd.

  32. Additional example for class discussion

  33. America’s Most Wanted: Threats to Internal and External Validity

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