liitännäisanalyysi

Liitännäisanalyysi, known in English as "appendage analysis" or "ancillary analysis," refers to a set of statistical methods and techniques used to analyze data that is secondary or supplementary to a primary research question. This type of analysis is often performed after the main objectives of a study have been met and the primary data has been analyzed. It can involve exploring unexpected findings, examining subgroups not originally planned for, or testing hypotheses that arose during the course of the research.

The purpose of liitännäisanalyysi is to extract additional insights from existing data, potentially leading to new research questions or a deeper understanding of the subject matter. It is important to distinguish liitännäisanalyysi from the primary analysis. Primary analysis is pre-specified and directly addresses the study's main objectives. Liitännäisanalyysi, on the other hand, is often exploratory and may not be driven by a priori hypotheses.

While valuable, liitännäisanalyysi carries certain risks. Because these analyses are not planned in advance, there is a higher chance of finding statistically significant results purely by chance, a phenomenon known as p-hacking or data dredging. Therefore, findings from liitännäisanalyysi should generally be considered hypothesis-generating rather than definitive proof. Subsequent studies are often needed to confirm any intriguing results discovered through liitännäisanalyysi. Researchers must carefully document all liitännäisanalyysi performed to ensure transparency and reproducibility.