Regression With Missing X's : A Review

  • Sheppard J
  • Osborne M
  • Chapman D
 et al. 
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Abstract

PURPOSE: This study develops and evaluates a multi-factorial model, based on landing performance, to estimate injury risk for surfing athletes.

METHODS: Five measures were collected from 78 competitive surfing athletes and then used to create a model to serve as a screening tool for landing tasks and potential injury risk. In the second part of the study, the model was evaluated using junior surfing athletes (n=32) with a longitudinal follow-up of their injuries over 26 weeks. Two models were compared based on the collected data, and magnitude based inferences were applied to determine the likelihood of differences between injured and non-injured groups.

RESULTS: The study resulted in a model based on five measures: (i) ankle dorsiflexion range of motion, (ii) isometric mid-thigh pull lower body strength, (iii) time to stabilisation during a drop and stick (DS) landing, (iv) relative peak force during a DS landing, and (v) frontal plane DS landing video analysis; for male and female professional surfers, and male and female junior surfers. Evaluation of the model showed that a scaled probability score was more likely to detect injuries in junior surfing athletes, and reported a correlation of r=0.66, p=0.001 with a model of equal variable importance. The injured (n=7) surfers had a lower probability score (0.18 ± 0.16) compared to the non-injured group (n=25, 0.36 ± 0.15), with 98% likelihood, Cohen's d=1.04.

CONCLUSIONS: The proposed model seems sensitive, easy to implement and interpret. Further research is recommended to show full validity potential adaptations for other sports.

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Authors

  • Jeremy M. Sheppard

  • Mark Osborne

  • Dale W Chapman

  • Mark Andrews

  • Phil Mcnamara

  • Josh L. Secomb

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