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Subject AUC AUC Cmax Cmax Test Ref Test Ref 2 150.12 142.29 5.145 3.216 4 36.95 5.00 2.442 0.498 6 24.53 26.05 1.442 2.728 7 22.11 34.64 2.007 3.309 9 703.83 476.56 15.133 11.155 12 217.06 176.02 9.433 8.446 14 40.75 152.40 1.787 6.231 16 52.76 51.57 3.570 2.445 17 101.52 23.49 4.476 1.255 19 37.14 30.54 2.169 2.613 22 143.45 42.69 5.182 3.031 23 29.80 29.55 1.714 1.804 25 63.03 92.94 3.201 5.645 28 . . 0.891 0.531 29 56.70 21.03 2.203 1.514 30 61.18 66.41 3.617 2.130 33 1376.02 1200.28 27.312 22.068 34 115.33 135.55 4.688 7.358 38 17.34 40.35 1.072 2.150 40 62.23 64.92 3.025 3.041 41 48.99 61.74 2.706 2.808 42 53.18 17.51 3.240 1.702 46 . . 1.680 . 48 98.03 236.17 3.434 7.378 49 1070.98 1016.52 21.517 20.116 log(Cmax) as needed for the TOST analysis is given below, where we fit a mixed model using SAS proc mixed. This model fits a random term for subjects within sequences. Using a mixed model we can produce an analysis that includes the data from all subjects, including those with only one value for AUC or Cmax. However, including the subjects with only one response does not change the results in any significant way and so we will report the results obtained using the subsets of data that have values in both periods for AUC (45 subjects) and Cmax (47 subjects).
DOI link for Subject AUC AUC Cmax Cmax Test Ref Test Ref 2 150.12 142.29 5.145 3.216 4 36.95 5.00 2.442 0.498 6 24.53 26.05 1.442 2.728 7 22.11 34.64 2.007 3.309 9 703.83 476.56 15.133 11.155 12 217.06 176.02 9.433 8.446 14 40.75 152.40 1.787 6.231 16 52.76 51.57 3.570 2.445 17 101.52 23.49 4.476 1.255 19 37.14 30.54 2.169 2.613 22 143.45 42.69 5.182 3.031 23 29.80 29.55 1.714 1.804 25 63.03 92.94 3.201 5.645 28 . . 0.891 0.531 29 56.70 21.03 2.203 1.514 30 61.18 66.41 3.617 2.130 33 1376.02 1200.28 27.312 22.068 34 115.33 135.55 4.688 7.358 38 17.34 40.35 1.072 2.150 40 62.23 64.92 3.025 3.041 41 48.99 61.74 2.706 2.808 42 53.18 17.51 3.240 1.702 46 . . 1.680 . 48 98.03 236.17 3.434 7.378 49 1070.98 1016.52 21.517 20.116 log(Cmax) as needed for the TOST analysis is given below, where we fit a mixed model using SAS proc mixed. This model fits a random term for subjects within sequences. Using a mixed model we can produce an analysis that includes the data from all subjects, including those with only one value for AUC or Cmax. However, including the subjects with only one response does not change the results in any significant way and so we will report the results obtained using the subsets of data that have values in both periods for AUC (45 subjects) and Cmax (47 subjects).
Subject AUC AUC Cmax Cmax Test Ref Test Ref 2 150.12 142.29 5.145 3.216 4 36.95 5.00 2.442 0.498 6 24.53 26.05 1.442 2.728 7 22.11 34.64 2.007 3.309 9 703.83 476.56 15.133 11.155 12 217.06 176.02 9.433 8.446 14 40.75 152.40 1.787 6.231 16 52.76 51.57 3.570 2.445 17 101.52 23.49 4.476 1.255 19 37.14 30.54 2.169 2.613 22 143.45 42.69 5.182 3.031 23 29.80 29.55 1.714 1.804 25 63.03 92.94 3.201 5.645 28 . . 0.891 0.531 29 56.70 21.03 2.203 1.514 30 61.18 66.41 3.617 2.130 33 1376.02 1200.28 27.312 22.068 34 115.33 135.55 4.688 7.358 38 17.34 40.35 1.072 2.150 40 62.23 64.92 3.025 3.041 41 48.99 61.74 2.706 2.808 42 53.18 17.51 3.240 1.702 46 . . 1.680 . 48 98.03 236.17 3.434 7.378 49 1070.98 1016.52 21.517 20.116 log(Cmax) as needed for the TOST analysis is given below, where we fit a mixed model using SAS proc mixed. This model fits a random term for subjects within sequences. Using a mixed model we can produce an analysis that includes the data from all subjects, including those with only one value for AUC or Cmax. However, including the subjects with only one response does not change the results in any significant way and so we will report the results obtained using the subsets of data that have values in both periods for AUC (45 subjects) and Cmax (47 subjects).
ABSTRACT