Simulate data for minimisation simulations
simulate_data.RdGiven a list of factors with specified levels and proportions, and a sample
size, this function simulates data for use in simulate_mini().
Arguments
- sampsize
the desired sample size of the data, i.e., the sample size of your prospective trial.
- factors
a list of factors, each a list containing two items. The first is
levelswhich is either a vector of the level names OR the number of levels. The second item is eitherprops, a vector of proportions equal to the number of levels in the factor; OR prop.dist which is a named vector containing the mean and sd of the proportions.- eligibility
logical, should the data include group eligibility. If
TRUEthen must supplygroupsargument.- groups
either a character vector of group names or an integer specifying the number of groups.
Examples
simulate_data(factors = list(sex = list(levels = c("M", "F"),
props = c(0.5, 0.5)),
site = list(levels = 12,
prop.dist = c(mean = 0.1, sd = 0.05))),
sampsize = 150)
#> ID sex site
#> 1 1 M 7
#> 2 2 F 8
#> 3 3 M 5
#> 4 4 M 2
#> 5 5 F 11
#> 6 6 M 2
#> 7 7 M 10
#> 8 8 M 8
#> 9 9 M 3
#> 10 10 F 10
#> 11 11 M 11
#> 12 12 M 8
#> 13 13 F 2
#> 14 14 F 8
#> 15 15 F 1
#> 16 16 M 4
#> 17 17 F 12
#> 18 18 M 3
#> 19 19 M 7
#> 20 20 M 10
#> 21 21 F 11
#> 22 22 M 7
#> 23 23 M 10
#> 24 24 F 9
#> 25 25 M 10
#> 26 26 M 10
#> 27 27 M 1
#> 28 28 M 7
#> 29 29 F 2
#> 30 30 F 2
#> 31 31 F 2
#> 32 32 F 2
#> 33 33 M 9
#> 34 34 F 4
#> 35 35 M 11
#> 36 36 M 12
#> 37 37 M 10
#> 38 38 F 3
#> 39 39 M 2
#> 40 40 M 2
#> 41 41 M 3
#> 42 42 F 10
#> 43 43 M 10
#> 44 44 F 6
#> 45 45 F 10
#> 46 46 M 8
#> 47 47 M 7
#> 48 48 F 4
#> 49 49 M 4
#> 50 50 F 2
#> 51 51 M 9
#> 52 52 F 6
#> 53 53 M 9
#> 54 54 M 9
#> 55 55 M 2
#> 56 56 M 12
#> 57 57 F 5
#> 58 58 M 6
#> 59 59 M 6
#> 60 60 M 1
#> 61 61 F 9
#> 62 62 M 4
#> 63 63 M 12
#> 64 64 F 7
#> 65 65 M 5
#> 66 66 M 6
#> 67 67 F 10
#> 68 68 M 12
#> 69 69 F 2
#> 70 70 M 12
#> 71 71 M 5
#> 72 72 F 5
#> 73 73 M 10
#> 74 74 M 9
#> 75 75 F 2
#> 76 76 M 12
#> 77 77 M 3
#> 78 78 F 12
#> 79 79 F 5
#> 80 80 F 4
#> 81 81 F 8
#> 82 82 F 2
#> 83 83 F 10
#> 84 84 M 3
#> 85 85 M 9
#> 86 86 M 3
#> 87 87 F 1
#> 88 88 M 7
#> 89 89 F 10
#> 90 90 M 9
#> 91 91 F 7
#> 92 92 M 3
#> 93 93 M 2
#> 94 94 F 9
#> 95 95 F 7
#> 96 96 M 5
#> 97 97 F 6
#> 98 98 M 4
#> 99 99 M 2
#> 100 100 F 8
#> 101 101 M 2
#> 102 102 F 12
#> 103 103 M 9
#> 104 104 M 7
#> 105 105 M 2
#> 106 106 F 2
#> 107 107 F 7
#> 108 108 F 6
#> 109 109 M 8
#> 110 110 F 9
#> 111 111 F 12
#> 112 112 M 2
#> 113 113 F 2
#> 114 114 M 5
#> 115 115 F 2
#> 116 116 F 12
#> 117 117 M 4
#> 118 118 F 9
#> 119 119 M 8
#> 120 120 F 7
#> 121 121 M 11
#> 122 122 F 2
#> 123 123 F 8
#> 124 124 M 11
#> 125 125 M 10
#> 126 126 F 2
#> 127 127 F 2
#> 128 128 M 6
#> 129 129 F 3
#> 130 130 F 4
#> 131 131 M 2
#> 132 132 F 1
#> 133 133 F 3
#> 134 134 M 10
#> 135 135 M 7
#> 136 136 M 8
#> 137 137 F 1
#> 138 138 M 9
#> 139 139 F 12
#> 140 140 F 10
#> 141 141 F 1
#> 142 142 F 1
#> 143 143 F 12
#> 144 144 M 2
#> 145 145 M 4
#> 146 146 F 5
#> 147 147 M 10
#> 148 148 F 7
#> 149 149 F 10
#> 150 150 M 7
simulate_data(factors = list(sex = list(levels = c("M", "F"),
props = c(0.5, 0.5)),
site = list(levels = 12,
prop.dist = c(mean = 0.1, sd = 0.05))),
sampsize = 100, eligibility = TRUE, groups = 4)
#> ID sex site eligible
#> 1 1 F 2 ABCD
#> 2 2 M 5 ACD
#> 3 3 F 2 ABC
#> 4 4 F 10 BD
#> 5 5 F 7 ABD
#> 6 6 F 6 BCD
#> 7 7 M 2 BC
#> 8 8 M 1 ABC
#> 9 9 M 3 ABCD
#> 10 10 M 1 BC
#> 11 11 F 10 BCD
#> 12 12 M 5 CD
#> 13 13 F 7 AB
#> 14 14 M 3 CD
#> 15 15 F 7 CD
#> 16 16 M 8 ABCD
#> 17 17 F 2 AC
#> 18 18 M 7 CD
#> 19 19 F 3 ABD
#> 20 20 F 1 ABCD
#> 21 21 F 1 CD
#> 22 22 M 8 AD
#> 23 23 F 4 ABC
#> 24 24 F 9 ABD
#> 25 25 F 9 ABC
#> 26 26 M 5 BD
#> 27 27 M 12 CD
#> 28 28 M 5 BC
#> 29 29 F 2 BC
#> 30 30 M 5 ACD
#> 31 31 F 8 BC
#> 32 32 F 5 ABCD
#> 33 33 M 2 ABCD
#> 34 34 F 3 ACD
#> 35 35 M 8 ACD
#> 36 36 F 7 ABD
#> 37 37 M 10 ABCD
#> 38 38 F 9 BC
#> 39 39 M 7 ABD
#> 40 40 M 12 AC
#> 41 41 F 2 ABC
#> 42 42 F 2 BD
#> 43 43 M 2 BC
#> 44 44 F 5 ABC
#> 45 45 M 2 BC
#> 46 46 F 9 ABC
#> 47 47 M 4 AB
#> 48 48 F 1 AB
#> 49 49 F 3 ABD
#> 50 50 M 8 ABCD
#> 51 51 M 3 AD
#> 52 52 M 7 BCD
#> 53 53 F 2 ACD
#> 54 54 F 3 AD
#> 55 55 F 9 ABC
#> 56 56 M 5 ABC
#> 57 57 F 8 BD
#> 58 58 M 12 CD
#> 59 59 F 12 ABD
#> 60 60 M 9 ABC
#> 61 61 F 2 CD
#> 62 62 M 5 BCD
#> 63 63 F 10 ABD
#> 64 64 F 12 AC
#> 65 65 M 9 AC
#> 66 66 M 9 BD
#> 67 67 F 5 BD
#> 68 68 F 12 BCD
#> 69 69 M 12 AD
#> 70 70 M 3 BD
#> 71 71 F 5 ABCD
#> 72 72 F 10 ABCD
#> 73 73 M 5 AC
#> 74 74 M 2 BC
#> 75 75 M 2 ACD
#> 76 76 F 10 ABCD
#> 77 77 M 2 ACD
#> 78 78 F 5 BC
#> 79 79 F 10 BC
#> 80 80 F 8 ABD
#> 81 81 F 8 AD
#> 82 82 M 6 BD
#> 83 83 M 2 ABC
#> 84 84 M 2 BD
#> 85 85 M 5 BCD
#> 86 86 F 2 CD
#> 87 87 M 2 ABC
#> 88 88 F 6 ABCD
#> 89 89 M 2 BCD
#> 90 90 M 12 BCD
#> 91 91 F 7 AD
#> 92 92 M 6 BC
#> 93 93 M 3 ABCD
#> 94 94 M 9 AB
#> 95 95 F 4 BC
#> 96 96 F 2 ACD
#> 97 97 F 2 ACD
#> 98 98 F 3 AD
#> 99 99 F 9 BC
#> 100 100 M 8 ACD