What represents a type 2 error in biostatistics?

In biostatistics, a type 2 error, also known as a false negative, occurs when a study fails to detect a true effect or difference that actually exists. This means that the analysis incorrectly concludes that there is no significant difference or effect when in fact there is one. This type of error is critical to recognize in research, as it might lead to missed opportunities for treatment improvements or ineffective policies based on the mistaken belief that no real effect is present.

The correct identification of a type 2 error emphasizes the importance of ensuring that studies are adequately powered and designed to uncover true effects, which is essential in making informed decisions based on research findings.