In meta-analysis, it is common to have dependent effect sizes, such as several effect sizes from the same sample but measured at different times. Cheung and Chan proposed the adjusted-individual and adjusted-weighted procedures to estimate the degree of dependence and incorporate this estimate in the meta-analysis. The present study extends the previous study by examining the case of heterogeneous degree of dependence. Simulation results reveal that these two procedures again generated less biased estimates of the degree of heterogeneity than the commonly used samplewise procedure and were statistically more powerful to detect true variations. In addition, the adjusted-weighted procedure generated slightly less biased estimates of the degree of heterogeneity than the adjusted-individual weighted procedure across conditions. Future directions to further refine these procedures are discussed.