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Jason C. Immekus, Franklin Muntis and Daniela Terson de Paleville

. The least absolute shrinkage and selection operator (lasso; Tibshirani, 1996 ), a model-based approach that has received little attention in exercise science research, is demonstrated as an approach for the selection of predictors of students’ academic skills. The American College of Sport Medicine

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Arne Jaspers, Tim Op De Beéck, Michel S. Brink, Wouter G.P. Frencken, Filip Staes, Jesse J. Davis and Werner F. Helsen

interactions that are modeled among ELIs). Least Absolute Shrinkage and Selection Operator This technique is an advanced version of linear regression. 18 When setting the regression coefficients, least absolute shrinkage and selection operator (LASSO) contains a mechanism that biases many of the coefficients

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Keith R. Lohse

example of a least absolute shrinkage and selection operator (or LASSO) in their regression analyses. “Shrinkage” refers to the fact that ordinary least squares estimates are going to provide the strongest correspondence to the sample data that generate their estimates. Thus, on average, our r 2 values