329 research outputs found
The future of forecasting competitions: Design attributes and principles
Forecasting competitions are the equivalent of laboratory experimentation widely used in physical and life sciences. They provide useful, objective information to improve the theory and practice of forecasting, advancing the field, expanding its usage, and enhancing its value to decision and policymakers. We describe 10 design attributes to be considered when organizing forecasting competitions, taking into account trade-offs between optimal choices and practical concerns, such as costs, as well as the time and effort required to participate in them. Consequently, we map all major past competitions in respect to their design attributes, identifying similarities and differences between them, as well as design gaps, and making suggestions about the principles to be included in future competitions, putting a particular emphasis on learning as much as possible from their implementation in order to help improve forecasting accuracy and uncertainty. We discuss that the task of forecasting often presents a multitude of challenges that can be difficult to capture in a single forecasting contest. To assess the caliber of a forecaster, we, therefore, propose that organizers of future competitions consider a multicontest approach. We suggest the idea of a forecasting-“athlon” in which different challenges of varying characteristics take place
THE EFFECT OF MUSCLE STRENGTH NORMALIZATION PROCEEDURES ON DECISIONS TO RETURN TO SPORT
The objective of this study was to evaluate different methods of normalizing and reporting muscle strength for making decisions about return to sport following an anterior cruciate ligament injury. 42 participants performed 5 isometric knee extensions on an isokinetic dynamometer. The peak force as well as the rate of torque development were determined and expressed either as the average of 4 trials or the peak value. In addition, the limb symmetry index was determined for each condition and compared. Using the peak method resulted in significantly higher values (
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