This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: How much can we really trust a measurement? And how much data do researchers need to collect to draw reliable conclusions?
Mohammad Reza Seydi at Umeå University has developed and tested new statistical methods to provide better answers to those questions. When researchers compare how people move, it is not always enough to know whether there is a difference between two groups. It may also be important to identify when during the movement that difference occurs.
Seydi proposes a new way of calculating how many measurements are required to detect the specific differences a researcher is interested in. The calculation can, for example, be targeted at the part of a movement that is most important to investigate. This means that researchers can tailor the amount of data needed to what they actually want to detect when planning a study.
To understand why this is needed, consider what happens when a researcher measures a movement. When a knee bends during a jump, the angle changes from one moment to the next. The result is therefore not a single value, but an entire curve.
"Imagine measuring how your knee bends during a jump, or how the angle of a sprinter's hip moves back and forth with each step. The measurement is not a single number, but an entire curve, or a continuous function, that changes from moment to moment throughout the movement," Seydi says. This type of measurement is known as functional data and is used in fields such as biomechanics and medicine.
While well-established statistical methods have long existed for traditional data, methods for functional data are not yet as extensively developed and tested. Seydi's research also shows that the ability to detect differences in such data is influenced by how researchers define what should count as a statistically detectable difference. This forms the basis for the new way of calculating how much data a study requires.
Extract — continue reading at the source.
