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Statistical Model Usage Guidelines for Data Analysis

Understand best practices in model creation and variable selection. Avoid using insignificant regressors and numeric identifiers without relationships. Properly define variables as X1, X2, etc., for clarity. Ensure estimates have standard errors for accurate analysis. Use simple letters in subscripts for variable definitions.

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Statistical Model Usage Guidelines for Data Analysis

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  1. Unusable Models

  2. James Insignificant regressor Insignificant regressor

  3. Kandrack & Marchand Model: 1976.01-2003.12 Insignificant regressor

  4. Lyle Do not use numeric identifiers unless there is some relationship among the variables. E.g., Inflation, Inflation squared, etc. Even then, the variables should be listed as X1, X2, etc. Putting the number in the subscript confuses the interpretation of t. Estimates without standard errors are useless.

  5. Peck, Petrovich, Redshaw, Steckel Let t = 2004.06 Ct-12 = Inflation from 2004.05 to 2004.06? What is this? What is this? What is this?

  6. Let t = 2004.06 unempt-12 = unemployment rate from 2004.06 to 2005.05? What does it mean, “unemployment from…” Lauren Mondschein

  7. Usable but Annoying Models

  8. Micciulla, Barnes, Cocco The table is for definitions, not explanations. You are not measuring to an accuracy of 1 part per 10 million, so do not report to an accuracy of 1 part per 10 million. Do not use programming notation.

  9. Fitzpatrick Subscript Single letters are preferable. This variable is not defined.

  10. Christy Werwie zt=α+β1xt-12+ β3wt-12+ut Do not use programming notation.

  11. Bowen

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