Transforming ANOVA and Regression Statistics for Meta-analysis

A methodological guide for converting common statistical summary measures like P-values, LSD, and CI into variance estimates suitable for meta-analysis. The resource, authored by David LeBauer and hosted on Papers with Code, focuses on agricultural and biological research contexts. It provides rules for prioritizing direct variance estimates and transforming range statistics.

Use Cases

• Integrate studies reporting only P-values into a meta-analysis based on the described conversion methods.
• Weight studies appropriately in an overall analysis using overestimated variance from transformed LSD statistics.
• Extract standard error from figures or tables as described for studies lacking direct variance reports.

Strengths

• Provides clear methodological guidance for a specific statistical integration problem.
• Authored by a named individual (David LeBauer) and hosted on a reputable academic platform (Papers with Code).
• Explicitly discusses the trade-offs of using overestimated variance in meta-analysis models.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The actual data content and example transformations are not provided in the input.

Provenance

Source

David LeBauer via Papers with Code

Collection Method

Methodological compilation and description for statistical conversion.