The Dantzig selector was recently proposed to perform variable selection and model fitting in the linear regression model. It can be solved numerically by the alternating direction method of multipliers (ADM); and in this paper, we show that the application of ADM to the Dantzig selector can be speeded up significantly if one of its resulting subproblems at each iteration is linearized. The resulting linearized ADM for the Dantzig selector is shown to be efficient for solving both synthetic and real world data sets.