![]() ![]() ![]() In these cases, metrics about the internal structure are not relevant. Studies with sensors have typically used single indicators, or the indicators simply provide an operational measure (Chaffin et al., 2017). This is an area where close collaboration between computer scientists (with skills to analyse sensor data) and sport scientists (with theories and understandings of human performance and expertise) will be useful for making sense of what information is valuable, where technology has to go to create valuable information, and what observed patterns actually mean, b Internal (factorial) structure. Woo, Tay, Jebb, and colleagues (2020) discussed three ways in which the validity of big data measurements can be evaluated:Ī Response processes (i.e., the congruence between the construct and the nature of response engaged in by participants). It is important to note that ‘more’ data does not necessarily improve the quality of measurement in research. Adjerid and Kelley (2018) alerted us to the fact that measurement quality needs to be improved for rigorous scientific work with big data. Big data sources include practical and ethical challenges, such as privacy, data security and storage, data sharing and validity, and replicability issues. ![]()
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