What is a characteristic feature of the Dunnett test?

The Dunnett test is specifically designed for comparing multiple experimental groups to a single control group. This method is particularly useful in situations where researchers want to assess the differences between treatment conditions and a baseline without increasing the overall type I error rate that occurs when performing multiple comparisons.

By focusing on one control group, the Dunnett test allows for a more precise evaluation of how each experimental condition differs from that baseline, making it a powerful tool in experimental design. This makes it distinct from tests that compare every group against all other groups, which could lead to increased chances of finding statistically significant results merely due to the number of comparisons being made.

The characteristics of the other options do not align with the purpose or methodology of the Dunnett test. For instance, comparing all group means refers to tests like ANOVA; using only paired samples limits the application unnecessarily, as the Dunnett test is primarily used with independent samples; and assessing overall model fit relates to model comparison techniques in statistics rather than specific comparison tests like the Dunnett.