In this paper, we investigate the problem of maximizing the weighted sum outage rate in multiuser multiple-input single-output (MISO) interference channels, where the transmitters have no knowledge of the exact values of channel coefficients, only the statistical information. Unfortunately, this problem is nonconvex and very difficult to deal with. We propose a new, provably convergent iterative algorithm where in each iteration, the original problem is approximated as second-order cone programming (SOCP) by introducing slack variables and using convex approximation. Simulation results show that the proposed SOCP algorithm converges in a few steps, and yields a better performance gain with a lower computational complexity than existing algorithms.