The present study evaluated the performance of robust variance estimation (RVE) and random-effects TSSEM with missing at random (MAR) data under realistic conditions. The performance of the two methods was compared in terms of the first stage of MASEM entailing the pooling of correlation estimates and in the second stage when the SEM model is estimated. Findings from this study indicated that RVE and TSSEM provided unbiased pooled correlations at the first stage of MASEM. And TSSEM and RVE both provided unbiased parameter estimates at the second stage. With MAR missing correlations, RVE provided acceptable coverage rates only in scenarios with at least 100 studies while TSSEM provided acceptable coverage rates even with a small to a moderate number of studies (k = 25 and 50).