Science with or without statistics: Discover-generalize-replicate? Discover-replicate-generalize?

Area of Science:

• Research Methodology
• Scientific Validity

Background:

• Overstated generalizability (external validity) is a frequent issue in scientific research.
• This often occurs alongside inflated effect sizes, statistical support, and disregard for internal validity concerns.

Purpose of the Study:

• To examine the relationship between generalizability and replication strategies.
• To analyze the impact of different approaches on the use and interpretation of inferential statistics.

Main Methods:

• Conceptual analysis of research validity frameworks.
• Exploration of two distinct strategic approaches: securing generalizability before replication versus replication preceding generalization.

Main Results:

• Overstated external validity can be linked to inflated effect sizes and dismissal of internal validity issues.
• Generalizability can be established before or after replication, influencing statistical approaches.
• Different strategic sequences present unique advantages and disadvantages regarding inferential statistics.

Conclusions:

• The timing of establishing generalizability relative to replication significantly impacts research validity.
• Researchers must carefully consider strategic sequencing to optimize the use of inferential statistics and ensure robust findings.