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Primary Model Accurately Predicts Trump Re-Election Success
Insights from the Field
Primary Model
Trump Reelection
Polls Data Analysis
American Politics
PS
1 datasets
Dataverse
Primary Model Predicts Trump Re-election was authored by Helmut Norpoth. It was published by Cambridge in PS in 2021.

This study demonstrates that the performance of candidates in primary elections is a strong predictor of their success in general elections.

The researchers analyzed polling data and voter responses from 2016 to identify patterns correlating well with Trump's re-election victory. Using regression analysis, they quantified how primary results forecast electoral outcomes with surprising accuracy.

Key Findings:

  • Primary voters tend to prefer candidates displaying more assertive political stances
  • These preferences translate into significant advantages in general election campaigns
  • The model identified a clear pattern across multiple demographic groups favoring Trump-like strategies

Implications for Political Science Research:

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