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Table 1 Power to detect an intervention effect (OR = 2.25) in scenario A with different methods of analysis

From: Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study

ICC k n jk True time effect OR = 1 True time effect OR = 1.227
GEE GLMM Cluster summaries method Fixed effects model GEE GLMM Cluster summaries method Fixed effects model
0.01 3 100 0.806 0.765 0.657 0.735 0.858 0.828 0.670 0.801
6 50 0.813 0.802 0.740 0.737 0.866 0.852 0.785 0.812
100 0.971 0.965 0.929 0.955 0.979 0.980 0.945 0.969
9 50 0.929 0.926 0.907 0.893 0.948 0.947 0.920 0.930
100 0.998 0.998 0.993 0.996 0.999 0.999 0.995 0.998
18 10 0.665 0.653 0.632 0.535 0.736 0.724 0.705 0.583
50 0.997 0.998 0.995 0.989 0.999 0.999 0.999 0.999
36 5 0.690 0.683 0.675 0.549 0.773 0.762 0.747 0.625
10 0.918 0.916 0.908 0.806 0.953 0.953 0.947 0.874
0.05 3 100 0.698 0.690 0.464 0.684 0.734 0.733 0.401 0.750
6 50 0.697 0.702 0.590 0.695 0.764 0.766 0.563 0.749
  100 0.925 0.929 0.810 0.923 0.962 0.966 0.758 0.961
9 50 0.859 0.863 0.782 0.860 0.900 0.904 0.755 0.899
  100 0.984 0.983 0.951 0.982 0.996 0.995 0.934 0.995
18 50 0.987 0.986 0.978 0.986 0.998 0.999 0.985 0.998
36 10 0.826 0.820 0.807 0.778 0.874 0.871 0.848 0.832
0.1 3 100 0.597 0.619 0.320 0.621 0.659 0.685 0.229 0.692
6 50 0.623 0.647 0.475 0.645 0.699 0.719 0.399 0.715
  100 0.871 0.888 0.673 0.892 0.919 0.936 0.534 0.932
9 50 0.811 0.827 0.693 0.820 0.847 0.860 0.599 0.850
  100 0.968 0.971 0.865 0.970 0.979 0.984 0.765 0.984
18 50 0.985 0.987 0.964 0.986 0.992 0.992 0.941 0.992
  100 1.000 1.000 0.999 1.000 1.000 1.000 0.986 1.000
36 10 0.763 0.766 0.740 0.752 0.838 0.832 0.793 0.808
  1. Only scenarios where at least one method had a power of between 0.7 and 1 are shown. Each estimate is based on 2000 simulations. All methods adjust for time in the model