We consider a longitudinal data (data over time for multiple patients) on recovery of IQ after coma of varying duration for 200 subjects. Each row provides information about the following patient characteristics: id: patient ID number. days: number of days post coma at which IQs were measured. duration: duration of the coma in days. sex: a factor with levels Female and Male. age: in years at the time of injury. piq: IQ for performance on a particular non-verbal task, such as, mathematical task. viq: verbal IQ. This question is related to the improvement of piq and viq over time and whether the improvement differs between young and old. Carry out a hypothesis test to assess this. State your assumptions (including type-I error rate prior to conducting the test). Interpret your results and conclusions in plain language. Do you think your conclusions are appropriate? What could influence your conclusions? Based on what you have learned in this course, can you describe what you could do to address the issues that you laid out (you don't have to solve this part, but present your way of thinking logically to address this problem)? 50 35 9 9 255 14 49 3333 3337 1093 187 438 97 352 2191 1569 14 86 101 78 97 98 93 105 117 90 28 101 80 84 84 97 94 112 126 129 101 112 103 99 28 28 180 3 42 40 98 14 14 14 0 88 89 108 101 108 51 76 2569 2600 2600 2638 2646 2646 2653 2653 2653 2662 2761 2773 2790 2826 2826 2826 2849 2849 2849 2882 2882 2882 3032 3032 3051 3058 3058 3226 3226 3226 3237 3237 3277 3346 3358 3358 3359 Male 18.71595 Male 43.93977 Male 43.93977 Male 16.56126 Male 22.91581 Male 22.91581 Male 30.00684 Male 30.00684 Male 30.00684 Male 28.08214 Female 24.36961 Male 6.513347 Male 48.80493 Male 23.2334 94 Male 23.2334 111 Male 23.2334 104 Male 20.08761 Male 20.08761 Male 20.08761 Male 19.2334 84 Male 19.2334 94 Male 19.2334 100 Male 16.93908 Male 16.93908 Male 37.24025 Male 22.25325 Male 22.25325 Male 27.45517 Male 27.45517 Male 27.45517 Male 49.85079 Male 49.85079 Male 37.47023 Female 57.27584 Male 20.67077 Male 20.67077 Female 56.89528 86 98 103 91 85 7631 211 290 636 1809 151 642 1040 141 262 1716 525 884 131 56 236 444 683 1123 18 18 18 20 20 13 28 28 0 0 0 9 9 1 90 103 79 87 68 65 85 76 89 87 93 79 75 88 64 78 81 67 82 96 85 89 97 91 65 88 67 79 104 79 87 97 84 189 51 44 30 175 59 18 4 4 9 We consider a longitudinal data (data over time for multiple patients) on recovery of IQ after coma of varying duration for 200 subjects. Each row provides information about the following patient characteristics: id: patient ID number. days: number of days post coma at which IQs were measured. duration: duration of the coma in days. sex: a factor with levels Female and Male. age: in years at the time of injury. piq: IQ for performance on a particular non-verbal task, such as, mathematical task. viq: verbal IQ. This question is related to the improvement of piq and viq over time and whether the improvement differs between young and old. Carry out a hypothesis test to assess this. State your assumptions (including type-I error rate prior to conducting the test). Interpret your results and conclusions in plain language. Do you think your conclusions are appropriate? What could influence your conclusions? Based on what you have learned in this course, can you describe what you could do to address the issues that you laid out (you don't have to solve this part, but present your way of thinking logically to address this problem)? 50 35 9 9 255 14 49 3333 3337 1093 187 438 97 352 2191 1569 14 86 101 78 97 98 93 105 117 90 28 101 80 84 84 97 94 112 126 129 101 112 103 99 28 28 180 3 42 40 98 14 14 14 0 88 89 108 101 108 51 76 2569 2600 2600 2638 2646 2646 2653 2653 2653 2662 2761 2773 2790 2826 2826 2826 2849 2849 2849 2882 2882 2882 3032 3032 3051 3058 3058 3226 3226 3226 3237 3237 3277 3346 3358 3358 3359 Male 18.71595 Male 43.93977 Male 43.93977 Male 16.56126 Male 22.91581 Male 22.91581 Male 30.00684 Male 30.00684 Male 30.00684 Male 28.08214 Female 24.36961 Male 6.513347 Male 48.80493 Male 23.2334 94 Male 23.2334 111 Male 23.2334 104 Male 20.08761 Male 20.08761 Male 20.08761 Male 19.2334 84 Male 19.2334 94 Male 19.2334 100 Male 16.93908 Male 16.93908 Male 37.24025 Male 22.25325 Male 22.25325 Male 27.45517 Male 27.45517 Male 27.45517 Male 49.85079 Male 49.85079 Male 37.47023 Female 57.27584 Male 20.67077 Male 20.67077 Female 56.89528 86 98 103 91 85 7631 211 290 636 1809 151 642 1040 141 262 1716 525 884 131 56 236 444 683 1123 18 18 18 20 20 13 28 28 0 0 0 9 9 1 90 103 79 87 68 65 85 76 89 87 93 79 75 88 64 78 81 67 82 96 85 89 97 91 65 88 67 79 104 79 87 97 84 189 51 44 30 175 59 18 4 4 9