Based on an extensive simulation study, McGregor et al. (Genome Biol 17:84, 2016) recommended the use of surrogate variable analysis (SVA) to control for confounding effects of cell-type heterogeneity in DNA methylation association studies in scenarios where no cell type proportions are available. As their recommendation was mainly based on simulated data, we sought to replicate findings in two large-scale empirical studies. In our empirical data SVA did not fully correct for cell-type effects, its performance was somewhat unstable, and carried a risk of missing true signals caused by removing variation that may be linked to actual disease processes. In contrast, a reference-based correction method performed well and did not show these limitations. A disadvantage of this approach is that if reference methylomes are not (publicly) available, they will need to be generated once for a small set of samples. However, given the notable risk we observed for cell type confounding, we argue that to avoid introducing false positive findings into the literature it may be well worth making this investment.