Abstract

In most epidemiological studies directed toward identifying major sports injury causation factors, injured athletes have been compared with uninjured athletes through single variable techniques. However, many of the factors highlighted in this proposal through these analytical techniques either interact or are interrelated. Multivariable statistical techniques have been used to detail risk factor interaction, such as discriminatory analysis and stepwise logistic regression. In this proposal, we will identify potential predictive factors that can be used in logistic regression equations, the basic concepts of this mathematical study, and equations that have been developed into what they are today. The purpose of regression techniques is two-fold: first, to estimate the relation between two variables, while taking the presence of other factors into account; second, to construct a model that allows for the prediction of the value of the dependent variable (in logistic regression, the probability of success) for specific values of a predicted group of variables.