Generate a Stochastic Enrollment and Dropout Schedule
stochastic_schedule.RdCreates a time-indexed schedule of enrollment and dropout events across arms by sampling inter-event times from user-supplied distribution functions. Each call produces a different realization, capturing natural variability in study timelines.
Value
data.frame with columns: time, arm, enroll (always 1),
drop (always 0 or 1). One row per subject event, sorted by arm,
then time.
Details
Use this when trial-duration variability is substantively important.
For a fixed, reproducible schedule see deterministic_schedule().
See also
deterministic_schedule() for piecewise-constant rates,
Timer$add_schedule() to attach to a Timer.
Examples
stochastic_schedule(
sample_size = 100,
arms = c("A", "B"),
allocation = c(2, 1),
enrollment = function(n) rexp(n, rate = 0.5),
dropout = function(n) rexp(n, rate = 0.1)
)
#> time arm enroll drop
#> 1 2.138888 A 1 0
#> 2 5.153133 A 1 0
#> 3 6.809122 A 1 0
#> 4 7.141244 A 1 0
#> 5 15.794766 A 1 0
#> 6 17.674250 A 1 0
#> 7 19.141605 A 1 0
#> 8 19.167919 A 0 1
#> 9 27.499409 A 1 0
#> 10 27.685114 A 1 0
#> 11 28.146922 A 0 1
#> 12 35.937856 A 1 0
#> 13 37.493785 A 1 0
#> 14 38.885187 A 1 0
#> 15 39.034750 A 1 0
#> 16 40.726927 A 1 0
#> 17 41.085161 A 0 1
#> 18 42.394469 A 0 1
#> 19 48.986946 A 0 1
#> 20 51.305409 A 1 0
#> 21 51.829223 A 0 1
#> 22 52.202823 A 1 0
#> 23 55.731013 A 1 0
#> 24 57.643810 A 1 0
#> 25 58.860835 A 1 0
#> 26 62.008714 A 1 0
#> 27 64.420644 A 0 1
#> 28 68.713206 A 1 0
#> 29 69.102620 A 1 0
#> 30 71.171258 A 1 0
#> 31 72.352946 A 1 0
#> 32 77.497755 A 1 0
#> 33 77.843506 A 1 0
#> 34 85.847857 A 1 0
#> 35 87.285035 A 1 0
#> 36 91.303265 A 0 1
#> 37 91.317525 A 1 0
#> 38 98.170226 A 1 0
#> 39 101.274155 A 1 0
#> 40 104.690755 A 1 0
#> 41 105.304466 A 1 0
#> 42 110.293065 A 1 0
#> 43 111.685587 A 1 0
#> 44 113.724258 A 1 0
#> 45 116.368706 A 1 0
#> 46 116.767295 A 0 1
#> 47 116.910177 A 1 0
#> 48 119.601329 A 1 0
#> 49 120.879197 A 1 0
#> 50 125.514770 A 0 1
#> 51 129.836557 A 1 0
#> 52 141.197623 A 1 0
#> 53 142.848979 A 1 0
#> 54 146.809684 A 0 1
#> 55 149.699507 A 1 0
#> 56 155.177160 A 1 0
#> 57 159.086000 A 1 0
#> 58 162.100666 A 1 0
#> 59 168.653439 A 1 0
#> 60 170.142104 A 1 0
#> 61 170.804506 A 1 0
#> 62 174.778502 A 0 1
#> 63 174.918456 A 0 1
#> 64 178.182842 A 1 0
#> 65 178.963263 A 1 0
#> 66 181.255650 A 1 0
#> 67 181.448627 A 1 0
#> 68 183.194996 A 1 0
#> 69 185.984909 A 1 0
#> 70 186.344516 A 1 0
#> 71 186.591218 A 1 0
#> 72 187.346103 A 1 0
#> 73 189.222563 A 1 0
#> 74 189.750071 A 1 0
#> 75 195.765972 A 1 0
#> 76 206.660424 A 1 0
#> 77 208.970692 A 1 0
#> 78 211.858075 A 0 1
#> 79 212.404234 A 1 0
#> 80 217.331796 A 0 1
#> 81 217.674780 A 1 0
#> 82 218.525097 A 0 1
#> 83 221.354350 A 0 1
#> 84 223.047336 A 1 0
#> 85 230.221254 A 0 1
#> 86 236.076021 A 0 1
#> 87 250.509163 A 0 1
#> 88 256.733910 A 0 1
#> 89 268.036853 A 0 1
#> 90 276.831528 A 0 1
#> 91 293.796791 A 0 1
#> 92 310.517306 A 0 1
#> 93 311.477191 A 0 1
#> 94 328.470589 A 0 1
#> 95 338.505490 A 0 1
#> 96 342.897235 A 0 1
#> 97 351.509292 A 0 1
#> 98 374.441441 A 0 1
#> 99 446.839784 A 0 1
#> 100 450.578695 A 0 1
#> 101 477.612773 A 0 1
#> 102 495.319160 A 0 1
#> 103 504.503082 A 0 1
#> 104 516.230845 A 0 1
#> 105 543.723713 A 0 1
#> 106 544.742167 A 0 1
#> 107 563.369574 A 0 1
#> 108 570.385301 A 0 1
#> 109 627.918899 A 0 1
#> 110 655.253946 A 0 1
#> 111 673.914334 A 0 1
#> 112 681.721414 A 0 1
#> 113 710.198273 A 0 1
#> 114 731.889734 A 0 1
#> 115 738.417387 A 0 1
#> 116 744.435744 A 0 1
#> 117 748.990998 A 0 1
#> 118 768.600725 A 0 1
#> 119 775.151957 A 0 1
#> 120 804.038857 A 0 1
#> 121 813.043690 A 0 1
#> 122 828.739905 A 0 1
#> 123 869.436383 A 0 1
#> 124 873.808618 A 0 1
#> 125 883.280805 A 0 1
#> 126 929.880265 A 0 1
#> 127 954.419451 A 0 1
#> 128 960.813101 A 0 1
#> 129 964.872692 A 0 1
#> 130 966.227659 A 0 1
#> 131 970.653844 A 0 1
#> 132 975.702729 A 0 1
#> 133 987.891104 A 0 1
#> 134 1004.293969 A 0 1
#> 135 1010.929775 A 0 1
#> 136 1024.075802 A 0 1
#> 137 1.441442 B 1 0
#> 138 1.980644 B 1 0
#> 139 10.554247 B 1 0
#> 140 26.703948 B 0 1
#> 141 27.035571 B 1 0
#> 142 30.082964 B 1 0
#> 143 33.829521 B 1 0
#> 144 36.576342 B 1 0
#> 145 39.877434 B 1 0
#> 146 48.583798 B 1 0
#> 147 58.862487 B 1 0
#> 148 68.612242 B 0 1
#> 149 71.059542 B 1 0
#> 150 76.717672 B 1 0
#> 151 81.167062 B 1 0
#> 152 85.618107 B 1 0
#> 153 91.372649 B 1 0
#> 154 94.813789 B 1 0
#> 155 95.091200 B 1 0
#> 156 103.958714 B 1 0
#> 157 106.241449 B 1 0
#> 158 107.471445 B 1 0
#> 159 107.980994 B 0 1
#> 160 111.293453 B 0 1
#> 161 118.144625 B 1 0
#> 162 133.863819 B 1 0
#> 163 143.601087 B 1 0
#> 164 147.052167 B 1 0
#> 165 156.104332 B 0 1
#> 166 156.807975 B 1 0
#> 167 160.546253 B 1 0
#> 168 171.475067 B 1 0
#> 169 189.644911 B 1 0
#> 170 205.572786 B 1 0
#> 171 209.258987 B 1 0
#> 172 210.074238 B 1 0
#> 173 210.703123 B 1 0
#> 174 218.524195 B 1 0
#> 175 237.787332 B 0 1
#> 176 266.407906 B 0 1
#> 177 308.082786 B 0 1
#> 178 327.279672 B 0 1
#> 179 387.024716 B 0 1
#> 180 435.392063 B 0 1
#> 181 440.305474 B 0 1
#> 182 458.567762 B 0 1
#> 183 461.751720 B 0 1
#> 184 539.460709 B 0 1
#> 185 559.474342 B 0 1
#> 186 567.806745 B 0 1
#> 187 578.173133 B 0 1
#> 188 615.294177 B 0 1
#> 189 645.536789 B 0 1
#> 190 668.727620 B 0 1
#> 191 702.719175 B 0 1
#> 192 737.031704 B 0 1
#> 193 768.012610 B 0 1
#> 194 770.573496 B 0 1
#> 195 797.512226 B 0 1
#> 196 830.111280 B 0 1
#> 197 850.148989 B 0 1
#> 198 898.214959 B 0 1
#> 199 996.342987 B 0 1
#> 200 996.976654 B 0 1