monitarkkuus

Monitarkkuus refers to the practice of performing multiple statistical tests or analyses on the same dataset or the same group of subjects. This is a common occurrence in fields such as medical research, genetics, and social sciences where researchers may explore numerous variables or hypotheses simultaneously. While it might seem beneficial to glean as much information as possible from a dataset, performing multiple tests without proper adjustment can lead to an inflated risk of false positives, also known as Type I errors. A false positive occurs when a null hypothesis is incorrectly rejected, meaning a significant finding is reported when, in reality, no true effect exists.

The core issue with monitarkkuus is that the probability of making at least one Type I error increases with the number of tests conducted. For instance, if a researcher conducts 20 independent tests, each at a significance level of 0.05 (meaning there's a 5% chance of a false positive for each individual test), the overall probability of obtaining at least one false positive across all 20 tests is considerably higher than 5%. Statistical methods exist to address this problem, collectively known as multiple comparison corrections. These methods aim to control the overall error rate, ensuring that the probability of making any Type I errors across the entire set of tests remains at a desired level, typically 0.05. Common techniques include the Bonferroni correction, the Holm-Bonferroni method, and False Discovery Rate (FDR) control. Researchers must carefully consider the implications of monitarkkuus and apply appropriate corrections to maintain the validity and reliability of their findings.