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Chevy versus Ford NASCAR Race Effect Size – A Meta-Analysis PowerPoint PPT Presentation

Chevy versus Ford NASCAR Race Effect Size – A Meta-Analysis Data Description All 256 NASCAR Races for 1993-2000 Season Race Finishes Among all Ford and Chevy Drivers (Ranks) Ford: 5208 Drivers (20.3 per race) Chevrolet: 3642 Drivers (14.2 per race)

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Chevy versus Ford NASCAR Race Effect Size – A Meta-Analysis

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Chevy versus ford nascar race effect size a meta analysis l.jpg

Chevy versus Ford NASCAR Race Effect Size – A Meta-Analysis


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Data Description

  • All 256 NASCAR Races for 1993-2000 Season

  • Race Finishes Among all Ford and Chevy Drivers (Ranks)

    • Ford: 5208 Drivers (20.3 per race)

    • Chevrolet: 3642 Drivers (14.2 per race)

  • For each race, Compute Wilcoxon Rank-Sum Statistic (Large-sample Normal Approximation)

  • Effect Size = Z/SQRT(NFord + NChevy)


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Wilcoxon Rank-Sum Test (Large-Sample)


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Evidence that Chevrolet tends to do better than Ford


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Effect Sizes Appear to be approximately Normal


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Combining Effect Sizes Across Races

  • Weighted Average of Race-Specific Effect Sizes

  • Weight Factor  1/V(di) = 1/Ni = 1/(NFord,i+NChevy,i)


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Test for Homogeneity of Effect Sizes


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Testing for Year Effects


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Testing for Year Effects


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Testing for Year and Race/Track Effects

  • Regression Model Relating Effect Size to:

    • Season (8 Dummy Variables (No Intercept))

    • Track Length

    • Number of Laps

    • Race Length (Track Length x # of Laps)

  • Weighted Least Squares with weighti = Ni


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Regression Coefficients/t-tests

Controlling for all other predictors, none appear significant


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C2 – Tests for Sub-Models and Overall


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Sources

  • Hedges, L.V. and I. Olkin (1985). Statistical Methods for Meta-Analysis, Academic Press, Orlando, FL.

  • Winner, L. (2006). “NASCAR Winston Cup Race Results for 1975-2003,” Journal of Statistical Education, Volume 14, #3 www.amstat.org/publications/jse/v14n3/datasets.winner.html


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