Power comparison with dependent data

We set correlation equal to c(1,0.25,0.3) in power calculation.

  1. reg
##       0.1    0.2   0.3    0.4    0.5
## 5  0.4800 0.6800 0.800 0.7800 0.8400
## 10 0.3200 0.4500 0.500 0.5000 0.5600
## 15 0.2267 0.4267 0.480 0.3533 0.4133
## 20 0.2350 0.3900 0.425 0.3900 0.3300
## 25 0.2440 0.2760 0.340 0.2360 0.3240
  1. smo
##      0.1   0.2   0.3    0.4    0.5
## 5  0.280 0.560 0.800 0.9400 0.9800
## 10 0.230 0.470 0.690 0.8100 0.9100
## 15 0.300 0.360 0.440 0.6533 0.5133
## 20 0.190 0.450 0.370 0.5350 0.4150
## 25 0.228 0.348 0.368 0.4080 0.4480
  1. difference
##         0.1      0.2    0.3   0.4   0.5
## 5  -0.20000 -0.12000  0.000 0.160 0.140
## 10 -0.09000  0.02000  0.190 0.310 0.350
## 15  0.07333 -0.06667 -0.040 0.300 0.100
## 20 -0.04500  0.06000 -0.055 0.145 0.085
## 25 -0.01600  0.07200  0.028 0.172 0.124
  1. reg
##       0.1    0.2    0.3    0.4   0.5
## 5  0.3640 0.7080 0.8280 0.8560 0.864
## 10 0.3160 0.4980 0.5940 0.5780 0.636
## 15 0.3213 0.4067 0.4533 0.4493 0.492
## 20 0.2680 0.3760 0.3820 0.3870 0.380
## 25 0.2432 0.3232 0.3312 0.3680 0.368
  1. smo
##       0.1    0.2    0.3    0.4    0.5
## 5  0.1960 0.4560 0.6600 0.7920 0.9360
## 10 0.1980 0.3100 0.3160 0.4120 0.4480
## 15 0.1440 0.1773 0.2200 0.2120 0.1467
## 20 0.1350 0.1330 0.1270 0.1380 0.1210
## 25 0.0984 0.0904 0.0992 0.0928 0.0856
  1. difference
##        0.1     0.2     0.3     0.4     0.5
## 5  -0.1680 -0.2520 -0.1680 -0.0640  0.0720
## 10 -0.1180 -0.1880 -0.2780 -0.1660 -0.1880
## 15 -0.1773 -0.2293 -0.2333 -0.2373 -0.3453
## 20 -0.1330 -0.2430 -0.2550 -0.2490 -0.2590
## 25 -0.1448 -0.2328 -0.2320 -0.2752 -0.2824

The differences of power between two methods are similar to previous calculation result. The power decreases if the data not independent.