Test of excess success (TES) is designed to identify sets of results within academic articles that are what?

• A. Too inconsistent to be plausible
• B. Too good to be true
• C. Not statistically significant
• D. Based on small samples

Answer: (B)

TES examines whether a group of study results contains more statistically significant findings than would be expected given the studies’ power and true effects. When many results come back with strong, p-values below the traditional threshold, and this pattern is unlikely under normal reporting and study conditions, it suggests the results are “excessively successful.” That is the idea behind the term excess success—findings that are too good to be true because they occur more often than the underlying data and methods would predict.

So the best description is: results that are too good to be true. This is not primarily about inconsistency across studies, lack of significance, or small sample size alone; it’s about a suspicious concentration of significant results that shouldn’t occur by chance given the study designs.