Prediction: the Lasso vs. just using the top 10 predictors

One incredibly popular tool for the analysis of high-dimensional data is the lasso. The lasso is commonly used in cases when you have many more predictors than independent samples (the n « p) problem. It is also often used in the context of prediction. Suppose you have an outcome Y and several predictors X1,…,XM, the lasso fits a model: Y = B + B1 X1 + B2 X2 + … + BM XM + E