The following data represent a study of family caregiving in Korea of older adults with dementia. The outcome variable,

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The Following Data Represent A Study Of Family Caregiving In Korea Of Older Adults With Dementia The Outcome Variable 1 (37.2 KiB) Viewed 75 times

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The following data represent a study of family caregiving in Korea of older adults with dementia. The outcome variable, caregiver burden (BURDEN), was measured by the Korean Burden Inventory (KBI) where scores ranged from 28 to 140 with higher scores indicating higher burden. Perform a stepwise regression analysis on the following independent variables reported by the researchers: CGAGE: caregiver age (years) CGINCOME: caregiver income (Won-Korean currency) CGDUR: caregiver-duration of caregiving (month) ADL: total activities of daily living where low scores indicate the elderly perform activities independently. MEM: memory and behavioral problems with higher scores indicating more problems. COG:cognitive impairment with lower scores indicating a greater degree of cognitive impairment. SOCIALSU: total score of perceived social support (25-175, higher values indicating more support). The reported data are as follows:
CGDUR 12 BURDEN 28 41 36 68 60 ADL 39 52 89 57 28 34 42 59 91 CGAGE CGINCOME 200 30 120 41 300 35 350 37 600 42 90 49 300 39 500 49 309 40 250 40 300 2 48 4 70 一一 38 46 17 26 52 57 89 48 70 60 74 78 43 76 49 55 27 39 39 44 33 42 52 48 53 40 35 26 16 30 60 36 10 24 18 30 10 12 32 48 12 24 36 12 11 8 60 19 48 36 MEM 4 33 17 31 35 3 16 6 41 24 22 41 9 33 36 17 14 35 33 13 34 28 12 57 51 20 20 88 90 38 83 30 45 47 90 63 34 76 26 68 85 22 82 80 80 81 30 450 300 309 250 260 250 200 200 200 300 300 300 200 150 180 200 300 COG SOCIALSU 18 119 9 131 3 141 7 150 19 142 25 148 172 147 13 98 3 147 13 146 11 97 24 139 14 127 18 132 0 142 16 131 141 106 18 144 26 119 10 122 110 3 121 3 18 101 1 117 17 129 27 142 22 23 ৩||| | 8 INI 2 72 61 63 77 85 31 79 92 76 91 78 103 99 73 NIS 16 142 47 SD919 33 41 43 27 27 88
137 72 46 9 15 63 25 35 35 45 36 52 45 77 42 60 41 24 12 6 7 24 60 6 36 96 6 30 30 2. 33 309 250 200 200 300 600 230 200 400 75 200 250 300 200 250 500 300 200 309 250 1000 300 300 49 89 72 45 73 0 22 13 18 0 19 11 14 15 0 3 19 3 15 21 18 6 23 18 15 15 5 11 52 26 57 10 34 14 30 64 31 24 13 16 17 13 42 7 17 13 32 50 44 57 40 45 48 50 31 33 30 36 45 32 55 50 37 40 40 49 37 148 135 144 128 148 141 151 124 105 117 111 146 99 115 119 134 165 101 148 132 120 129 133 64 52 71 41 85 52 68 57 84 91 83 73 57 69 81 71 91 48 94 30 58 33 O 6 12 60 24 20 30 21 12 18 34 90 48 47 32 63 76 79 48 57 49 88 54 309 18 9 73
38 33 87 47 41 33 28 33 34 40 54 32 6 20 11 25 18 20 11 24 21 31 30 5 60 18 12 120 18 18 12 32 66 40 22 17 20 27 250 200 1000 309 400 330 200 200 300 280 350 280 500 600 250 1000 200 450 200 44 47 60 65 57 85 28 40 87 80 49 57 32 52 42 22 90 55 83 50 44 79 24 40 35 55 45 46 37 47 28 61 35 68 80 15 9 28 19 121 117 140 117 138 163 157 143 125 161 142 135 137 133 131 144 136 169 127 21 17 17 24 44 42 44 25 41 28 24 14 24 84 21 3 29 23 30 49 12 120 8 31 65 29 21 7 26 6 10 PAL 65 63 89 67 50 12
8 13 43 3一8 14 47 70 40 47 44 37 36 55 45 30 22 18 16 18 27 14 99 53 78 112 四一四一四 9 18 33 25 16 」 RESS 17 13 0 52 23 42 0 后 ] 309 1000 300 309 300 200 2000 400 200 1000 200 230 200 200 100 150 300 200 250 30 100 300 200 200 120 200 150 309 12 12 24 54 12 12 12 14 36 12 36 36 30 12 12 60 60 48 6 24 36 48 18 48 2 66 96 19 43 53 60 63 28 35 37 82 88 52 30 69 52 59 53 65 90 88 66 60 48 82 88 63 15 16 49 17 38 22 56 12 42 12 38 41 25 47 35 59 49 51 54 53 49 44 36 64 18 12 20 17 21 110 120 115 101 139 153 111 131 139 132 147 171 145 140 139 133 145 122 133 107 118 95 100 125 116 124 132 152 68 63 49 42 56 46 72 95 57 88 81 104 的一思一加一码一码 一一一一一四一印一一一一一一一见一田一9A 2 0 21 14 Nm 一一一B一一一一础1598 6 23 7 13 13 14 5 88 四一四一%B8 115 66 41 24 49 34 on = 92 79 3 43 54 38 17 71 66 81 97 69 112 88 48 13 29 3 66 1
a. Fit the model describing the data using Minitab [2] b. Use stepwise regression to select the best model using Minitab and give 3 reasons for selecting the remaining variables [3] C. Test at the 0.05 level if the unselected variables can be dropped from the model [3] d. Validate your new model and use it for constructing 95% confidence and prediction intervals for all values of the independent variable. [5]