We will discuss multivariate multiple regression and adding covariates to MANOVA.
Responder_Type Individual Day_0 Day_1 Day_2 Day_7 Day_14 Day_28 log_0 log_1 log_2 log_7 log_14 log_28 Y 1 11414.9 17461.9 19303.3 11776.5 16481.6 18769.7 9.34267 9.7678 9.8680 9.3739 9.7100 9.8400 Y 2 11761.8 26143.5 24651.6 22734.7 16481.6 18769.7 9.37261 10.1714 10.1126 10.0316 9.7100 9.8400 Y 3 13664.3 26074.4 22826.3 18222.6 16155.2 18769.7 9.52254 10.1687 10.0357 9.8104 9.6900 9.8400 Y 4 11540.1 53371.2 61456.4 25517.4 26815.9 22790.4 9.35359 10.8850 11.0261 10.1471 10.1967 10.0341 Y 5 12081.6 21713.0 15061.9 18078.2 16990.9 18769.7 9.39944 9.9857 9.6199 9.8025 9.7404 9.8400 Y 6 9997.6 21122.8 18664.2 28093.0 17939.0 29943.9 9.21010 9.9581 9.8344 10.2433 9.7947 10.3071 Y 7 7507.8 21262.9 15972.3 16410.8 14589.2 17415.9 8.92369 9.9647 9.6786 9.7057 9.5880 9.7651 Y 8 8663.9 22601.0 18865.3 18441.0 18494.9 18851.7 9.06692 10.0257 9.8451 9.8223 9.8252 9.8444 Y 9 10706.0 22932.3 19430.3 22860.4 23034.1 19384.8 9.27856 10.0403 9.8746 10.0372 10.0447 9.8722 Y 10 11614.7 19930.5 21020.7 16272.9 15381.5 16397.6 9.36003 9.9000 9.9533 9.6973 9.6409 9.7049 Y 11 7802.8 25495.1 19997.9 18060.6 22315.5 23126.0 8.96224 10.1462 9.9034 9.8015 10.0130 10.0487 Y 12 11213.6 25262.6 18758.3 12626.1 11362.1 14796.9 9.32488 10.1371 9.8394 9.4435 9.3380 9.6022 Y 13 7521.9 18282.0 15244.6 10057.4 12532.0 14402.7 8.92557 9.8137 9.6320 9.2161 9.4360 9.5752 Y 14 10290.3 19072.7 20434.0 16148.9 16282.7 20384.0 9.23896 9.8560 9.9250 9.6896 9.6979 9.9225 Y 15 7518.6 21373.2 17259.6 14275.1 14281.1 14966.9 8.92513 9.9699 9.7561 9.5663 9.5667 9.6136 N 1 11693.3 20623.1 18839.2 23948.0 12456.5 13359.7 9.36677 9.9342 9.8437 10.0836 9.4300 9.5000 N 2 20489.0 56887.2 39841.9 43468.9 11498.8 13226.8 9.92765 10.9488 10.5927 10.6798 9.3500 9.4900 N 3 7599.7 20925.4 6854.2 9596.4 13722.0 11977.9 8.93586 9.9487 8.8326 9.1691 9.5268 9.3908 N 4 7475.1 19415.8 15230.0 6848.3 11161.2 15119.8 8.91934 9.8738 9.6310 8.8318 9.3202 9.6238 N 5 10536.5 10951.1 10996.7 13369.7 10599.3 14111.2 9.26260 9.3012 9.3054 9.5007 9.2685 9.5547 N 6 10056.6 17893.1 16079.3 9024.5 9527.8 16989.9 9.21598 9.7922 9.6853 9.1077 9.1620 9.7404 N 7 13547.0 16276.9 19004.6 13346.8 14270.3 23868.3 9.51392 9.6975 9.8524 9.4990 9.5659 10.0803 N 8 9225.6 15606.1 14296.7 8159.4 9728.2 10655.3 9.12973 9.6554 9.5678 9.0069 9.1828 9.2738 N 9 6928.8 19736.4 16362.1 22876.9 17034.6 8942.5 8.84345 9.8902 9.7027 10.0379 9.7430 9.0986 N 10 8199.4 21073.4 17104.9 14532.5 19080.1 16211.2 9.01182 9.9558 9.7471 9.5841 9.8564 9.6935 N 11 4650.1 21729.2 17025.4 16531.0 13747.7 19303.6 8.44464 9.9864 9.7425 9.7130 9.5286 9.8680 N 12 15412.9 13787.9 16970.1 9014.1 10419.9 9833.3 9.64296 9.5315 9.7392 9.1065 9.2515 9.1935 N 13 9633.2 12790.3 15948.7 14265.2 16672.7 8620.1 9.17297 9.4564 9.6771 9.5656 9.7215 9.0619 N 14 9776.1 15146.7 25677.6 8918.9 9816.2 14995.3 9.18769 9.6255 10.1534 9.0959 9.1918 9.6155 N 15 10396.0 14976.9 9150.4 2070.1 8064.8 11081.9 9.24918 9.6143 9.1216 7.6353 8.9953 9.3131 N 16 12738.2 14799.0 11447.3 12654.1 13134.8 11278.5 9.45236 9.6023 9.3455 9.4457 9.4830 9.3307 N 17 10548.1 22913.1 20334.0 17160.7 16512.1 17327.8 9.26370 10.0395 9.9200 9.7504 9.7118 9.7601 N 18 7783.7 19817.7 18347.2 14450.5 19288.9 13262.9 8.95979 9.8943 9.8172 9.5785 9.8673 9.4927