Type I error control for cluster randomized trials under varying small sample structures
Abstract Background Linear mixed models (LMM) are a common approach to analyzing data from cluster randomized trials (CRTs).Inference on parameters can be performed via Wald tests or likelihood ratio tests (LRT), but both approaches may give incorrect Type I error rates in common finite sample settings.The impact of different combinations of cluste