Abstract: In this paper, we studied the inverse probability weighted least squares estimation of single-index model with response variable missing at random. Firstly, the B-spline technique is used to approximate the unknown single-index function, and then the objective function is established based on the inverse probability weighted least squares method. By the two-stage Newton iterative algorithm, the estimation of index parameters and the B-spline coefficients can be obtained. Finally, through many simulation examples and a real data application, it can be concluded that the method proposed in this paper performs very well for moderate sample