Quarto Report Example
Written by jojo
Introduction
Here is a report showing how to create ixxxxxxxxxxxxxxxxxxx using plotly for xxxxxxxxxxxxxxxxxxxxxxxxxxxx.
The source code used to generate this report can be found in this GitHub page.
Background
Here is some background knowledge about the use of the xxxxxxxxxxxxxxxxxx.
blah
xxxxxxxxxxxxxxxxx webpage by xxxxxxxxxxxxxx
balah
- A raincloud plot [@xxxx2021] xxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxdetector saturation or [matrix effect]((https://www.google.com).
Simulation
Code
# trt type id milesone pre post (1:2,1:2,1:41,1:16)
#
# d <- expand.grid(trt=1:2, type =1:2, id=1:41, milestone=1:6)
#
# d$response <- rbinom(984,1,.2)
#
# d <- plyr:arrange(d,id, milestone, )
# design
intercept =100
top = 4
range1 = c(2, 10)
range2 = c(5, 10)
replicates = c(3, 10)
x1 <- range1[1]
x2 <- range1[2]
x3 <- range2[1]
x4 <- range2[2]
x5 <- replicates[1]
x6 <- replicates[2]
# SDs
a =20
b =2
c =2
d =2
# seems that I need to use both c(x1,x2) c(x1:x2) so sample function works correctly
if (x1==x2) {
middle <- sample(c(x1,x2), top, replace=TRUE) # ditto groups in each top level 6
} else {
middle <- sample(c(x1:x2), top, replace=TRUE) # ditto groups in each top level 6
}
if (x3==x4) {
lower <- sample(c(x3,x4), sum(middle), replace=TRUE )
} else {
lower <- sample(c(x3:x4), sum(middle), replace=TRUE )
}
if (x5==x6) {
replicates <- sample(c(x5,x6), sum(lower), replace=TRUE )
} else {
replicates <- sample(c(x5:x6), sum(lower), replace=TRUE )
}
N <- sum(replicates)
residual <- d
d <- intercept
# random effects
top.r <- rnorm(top, d, a)
middle.r <- rnorm(sum(middle), 0, b)
lower.r <- rnorm(sum(lower), 0, c)
# ids
lower.id <- rep(seq_len(sum(lower)), replicates )
middle.id <- cut(lower.id, c(0,cumsum(lower)), labels=FALSE)
top.id <- cut(middle.id, c(0,cumsum(middle)), labels=FALSE)
# --------------------------------------------------------------------------
Data <- data.frame( top=top.id, mid=middle.id, low=lower.id,
y= rnorm( sum(replicates), top.r[top.id] +
middle.r[middle.id] + lower.r[lower.id], residual ) )
df1 <- as.data.frame(Data)
df1> top mid low y
> 1 1 1 1 75.99231
> 2 1 1 1 74.01059
> 3 1 1 1 76.01964
> 4 1 1 1 72.67590
> 5 1 1 1 76.82426
> 6 1 1 1 75.19325
> 7 1 1 1 71.27415
> 8 1 1 1 75.79115
> 9 1 1 1 72.90155
> 10 1 1 2 69.68628
> 11 1 1 2 70.51956
> 12 1 1 2 66.51754
> 13 1 1 2 69.62235
> 14 1 1 2 71.40624
> 15 1 1 2 72.57818
> 16 1 1 2 73.59825
> 17 1 1 2 76.78654
> 18 1 1 2 73.98262
> 19 1 1 2 71.32676
> 20 1 1 3 74.65231
> 21 1 1 3 73.92414
> 22 1 1 3 74.05440
> 23 1 1 3 74.50301
> 24 1 1 3 77.77669
> 25 1 1 3 76.22699
> 26 1 1 3 76.57822
> 27 1 1 3 79.31613
> 28 1 1 4 72.51901
> 29 1 1 4 77.31805
> 30 1 1 4 73.45618
> 31 1 1 4 72.27405
> 32 1 1 4 73.39270
> 33 1 1 5 71.85474
> 34 1 1 5 73.08889
> 35 1 1 5 71.58119
> 36 1 1 5 70.25864
> 37 1 1 5 69.64913
> 38 1 1 5 73.63839
> 39 1 1 6 72.66953
> 40 1 1 6 72.22111
> 41 1 1 6 70.69981
> 42 1 1 6 67.13129
> 43 1 1 6 70.87632
> 44 1 1 6 73.18862
> 45 1 1 7 74.29058
> 46 1 1 7 66.99356
> 47 1 1 7 71.92639
> 48 1 1 7 72.22128
> 49 1 1 7 71.47243
> 50 1 1 7 71.38390
> 51 1 1 7 67.68559
> 52 1 1 7 72.27965
> 53 1 1 7 72.44369
> 54 1 1 7 73.79803
> 55 1 1 8 74.48572
> 56 1 1 8 70.73856
> 57 1 1 8 74.45946
> 58 1 1 8 76.09998
> 59 1 1 8 73.09459
> 60 1 1 8 74.54019
> 61 1 1 8 72.80790
> 62 1 1 8 76.22478
> 63 1 2 9 84.51988
> 64 1 2 9 77.51159
> 65 1 2 9 80.53183
> 66 1 2 9 73.43193
> 67 1 2 10 74.24724
> 68 1 2 10 74.00634
> 69 1 2 10 77.55809
> 70 1 2 10 74.57436
> 71 1 2 10 77.01896
> 72 1 2 10 75.31689
> 73 1 2 10 79.11759
> 74 1 2 10 78.43621
> 75 1 2 10 79.98493
> 76 1 2 11 77.54934
> 77 1 2 11 82.01986
> 78 1 2 11 82.13479
> 79 1 2 11 78.54233
> 80 1 2 11 80.43850
> 81 1 2 11 81.77966
> 82 1 2 11 77.22206
> 83 1 2 12 71.41871
> 84 1 2 12 75.82147
> 85 1 2 12 73.37943
> 86 1 2 13 77.52230
> 87 1 2 13 79.11591
> 88 1 2 13 79.98987
> 89 1 2 13 77.47903
> 90 1 2 14 80.42066
> 91 1 2 14 78.35149
> 92 1 2 14 76.08741
> 93 1 2 14 75.10485
> 94 1 2 14 74.20006
> 95 1 2 14 77.30079
> 96 1 2 14 78.30454
> 97 1 3 15 75.41546
> 98 1 3 15 75.79022
> 99 1 3 15 78.58493
> 100 1 3 15 75.38018
> 101 1 3 15 72.82033
> 102 1 3 15 78.02188
> 103 1 3 15 77.58877
> 104 1 3 15 75.20228
> 105 1 3 15 74.11433
> 106 1 3 15 75.46721
> 107 1 3 16 76.77703
> 108 1 3 16 80.06772
> 109 1 3 16 73.46654
> 110 1 3 17 73.63441
> 111 1 3 17 73.00182
> 112 1 3 17 73.47890
> 113 1 3 17 72.84821
> 114 1 3 17 76.25339
> 115 1 3 17 72.30296
> 116 1 3 17 72.42245
> 117 1 3 17 73.26632
> 118 1 3 18 77.99077
> 119 1 3 18 74.11853
> 120 1 3 18 78.92254
> 121 1 3 18 74.87281
> 122 1 3 18 76.70340
> 123 1 3 18 75.51507
> 124 1 3 18 81.29584
> 125 1 3 19 71.18339
> 126 1 3 19 74.93604
> 127 1 3 19 73.55043
> 128 1 3 19 77.00969
> 129 1 3 19 78.99117
> 130 1 3 20 79.27252
> 131 1 3 20 77.94933
> 132 1 3 20 79.63429
> 133 1 3 20 77.69979
> 134 1 3 20 76.27397
> 135 1 3 20 75.97925
> 136 1 3 20 78.86799
> 137 1 3 21 76.90064
> 138 1 3 21 73.71593
> 139 1 3 21 77.00751
> 140 1 3 21 75.65484
> 141 1 3 21 77.02595
> 142 1 3 22 77.61056
> 143 1 3 22 74.17915
> 144 1 3 22 74.63974
> 145 1 3 22 73.49154
> 146 1 3 22 76.64236
> 147 1 3 22 77.25044
> 148 1 4 23 78.37835
> 149 1 4 23 81.30461
> 150 1 4 23 77.92566
> 151 1 4 23 76.48555
> 152 1 4 23 71.94955
> 153 1 4 23 76.90298
> 154 1 4 23 79.50665
> 155 1 4 23 79.42985
> 156 1 4 23 77.98844
> 157 1 4 24 78.44119
> 158 1 4 24 74.96519
> 159 1 4 24 77.36868
> 160 1 4 24 74.34908
> 161 1 4 24 75.95646
> 162 1 4 25 74.40567
> 163 1 4 25 75.91909
> 164 1 4 25 75.27209
> 165 1 4 25 76.80938
> 166 1 4 25 78.41578
> 167 1 4 26 75.57335
> 168 1 4 26 72.27523
> 169 1 4 26 77.20267
> 170 1 4 26 76.79573
> 171 1 4 26 74.31362
> 172 1 4 27 73.22352
> 173 1 4 27 70.12306
> 174 1 4 27 71.42082
> 175 1 4 27 70.10505
> 176 1 4 27 74.34698
> 177 1 4 27 73.86174
> 178 1 4 27 70.26644
> 179 1 5 28 77.84822
> 180 1 5 28 75.50123
> 181 1 5 28 79.78537
> 182 1 5 28 77.78053
> 183 1 5 28 80.52957
> 184 1 5 28 74.90627
> 185 1 5 28 76.62192
> 186 1 5 29 75.39438
> 187 1 5 29 74.07894
> 188 1 5 29 74.96031
> 189 1 5 29 74.53307
> 190 1 5 29 74.69494
> 191 1 5 29 72.32950
> 192 1 5 29 74.96892
> 193 1 5 30 77.19286
> 194 1 5 30 76.65694
> 195 1 5 30 74.80445
> 196 1 5 30 76.52406
> 197 1 5 30 73.86255
> 198 1 5 30 77.61466
> 199 1 5 30 75.85083
> 200 1 5 30 73.86059
> 201 1 5 31 73.44781
> 202 1 5 31 80.78464
> 203 1 5 31 72.69151
> 204 1 5 31 73.57401
> 205 1 5 31 72.58254
> 206 1 5 32 82.07004
> 207 1 5 32 75.88058
> 208 1 5 32 78.00194
> 209 1 5 32 81.54525
> 210 1 5 32 80.02957
> 211 1 5 32 79.29319
> 212 1 5 32 78.27435
> 213 1 5 32 76.61443
> 214 1 5 32 77.86885
> 215 1 6 33 79.32265
> 216 1 6 33 76.11016
> 217 1 6 33 78.48388
> 218 1 6 33 80.96531
> 219 1 6 33 76.44980
> 220 1 6 34 79.49083
> 221 1 6 34 78.44165
> 222 1 6 34 79.81438
> 223 1 6 34 77.13073
> 224 1 6 34 77.93736
> 225 1 6 34 77.32115
> 226 1 6 34 79.01517
> 227 1 6 34 82.91437
> 228 1 6 34 80.48663
> 229 1 6 34 76.43017
> 230 1 6 35 79.32244
> 231 1 6 35 76.21359
> 232 1 6 35 76.78277
> 233 1 6 36 72.04576
> 234 1 6 36 79.07755
> 235 1 6 36 73.76151
> 236 1 6 37 70.45743
> 237 1 6 37 73.99114
> 238 1 6 37 75.93547
> 239 1 6 37 72.24626
> 240 1 6 37 69.63720
> 241 1 6 37 72.87503
> 242 1 6 37 72.63578
> 243 1 6 37 71.12305
> 244 1 6 37 74.04935
> 245 1 6 38 76.69011
> 246 1 6 38 77.28048
> 247 1 6 38 78.08219
> 248 1 6 38 79.86834
> 249 1 6 38 81.44602
> 250 1 6 38 79.56081
> 251 1 6 38 77.50437
> 252 1 6 39 79.40730
> 253 1 6 39 80.34396
> 254 1 6 39 79.98337
> 255 1 6 39 79.37753
> 256 1 6 39 78.13468
> 257 1 6 39 82.52254
> 258 1 6 39 80.45684
> 259 1 6 39 80.36959
> 260 1 6 39 79.97232
> 261 1 6 39 77.44794
> 262 1 6 40 77.67718
> 263 1 6 40 73.18714
> 264 1 6 40 71.82510
> 265 1 6 40 70.67395
> 266 1 6 41 75.40900
> 267 1 6 41 76.79247
> 268 1 6 41 77.44479
> 269 1 6 41 74.88488
> 270 1 6 41 75.11848
> 271 1 6 42 73.92138
> 272 1 6 42 75.06224
> 273 1 6 42 74.89012
> 274 1 6 42 77.61668
> 275 2 7 43 137.04146
> 276 2 7 43 136.32450
> 277 2 7 43 136.81527
> 278 2 7 43 134.42313
> 279 2 7 43 132.77063
> 280 2 7 43 135.45557
> 281 2 7 43 139.90956
> 282 2 7 43 134.95342
> 283 2 7 44 140.18948
> 284 2 7 44 138.49048
> 285 2 7 44 140.01117
> 286 2 7 44 140.00438
> 287 2 7 44 139.87382
> 288 2 7 44 137.84890
> 289 2 7 44 137.11920
> 290 2 7 44 138.33373
> 291 2 7 45 137.45779
> 292 2 7 45 140.34796
> 293 2 7 45 137.27264
> 294 2 7 45 139.47401
> 295 2 7 45 140.09485
> 296 2 7 45 139.34708
> 297 2 7 45 141.04515
> 298 2 7 45 141.69156
> 299 2 7 45 139.85913
> 300 2 7 45 140.16746
> 301 2 7 46 135.65511
> 302 2 7 46 136.64578
> 303 2 7 46 139.63844
> 304 2 7 46 135.12067
> 305 2 7 46 137.85219
> 306 2 7 46 137.04159
> 307 2 7 46 136.36874
> 308 2 7 46 136.12968
> 309 2 7 46 133.77053
> 310 2 7 47 136.20911
> 311 2 7 47 138.95016
> 312 2 7 47 136.48591
> 313 2 7 47 139.94779
> 314 2 7 47 139.52519
> 315 2 7 47 134.39050
> 316 2 7 47 137.31844
> 317 2 7 47 139.97481
> 318 2 7 48 130.35733
> 319 2 7 48 130.65444
> 320 2 7 48 131.36917
> 321 2 7 48 133.08910
> 322 2 7 48 135.55671
> 323 2 7 48 136.12457
> 324 2 7 48 135.47585
> 325 2 7 49 138.55784
> 326 2 7 49 141.07689
> 327 2 7 49 139.79758
> 328 2 7 49 135.74024
> 329 2 7 49 135.87401
> 330 2 7 49 140.84575
> 331 2 7 49 140.05247
> 332 2 7 50 138.02508
> 333 2 7 50 132.65129
> 334 2 7 50 132.93354
> 335 2 7 50 130.55919
> 336 2 7 51 140.76795
> 337 2 7 51 141.04030
> 338 2 7 51 139.14157
> 339 2 7 51 137.75243
> 340 2 7 51 138.25214
> 341 2 7 52 131.04330
> 342 2 7 52 129.84484
> 343 2 7 52 134.89405
> 344 2 7 52 135.21174
> 345 2 7 52 134.06505
> 346 2 7 52 132.73802
> 347 2 7 52 130.59901
> 348 2 7 52 133.66252
> 349 2 7 52 134.75198
> 350 2 7 52 134.74950
> 351 2 8 53 129.93039
> 352 2 8 53 131.13350
> 353 2 8 53 136.23847
> 354 2 8 53 131.53179
> 355 2 8 53 133.42424
> 356 2 8 53 134.08471
> 357 2 8 53 132.00347
> 358 2 8 53 134.16814
> 359 2 8 54 136.13174
> 360 2 8 54 136.67058
> 361 2 8 54 134.34523
> 362 2 8 54 136.73808
> 363 2 8 54 137.16021
> 364 2 8 54 134.25736
> 365 2 8 54 134.06636
> 366 2 8 54 134.90167
> 367 2 8 54 133.40344
> 368 2 8 55 132.69651
> 369 2 8 55 133.50795
> 370 2 8 55 135.43741
> 371 2 8 55 126.06795
> 372 2 8 55 132.02516
> 373 2 8 55 131.36101
> 374 2 8 55 131.20091
> 375 2 8 55 133.60829
> 376 2 8 55 129.25010
> 377 2 8 55 131.37025
> 378 2 8 56 134.11917
> 379 2 8 56 130.11364
> 380 2 8 56 136.07385
> 381 2 8 57 134.28919
> 382 2 8 57 130.34930
> 383 2 8 57 128.44633
> 384 2 8 57 135.42806
> 385 2 8 57 135.78052
> 386 2 8 57 133.03119
> 387 2 8 57 131.64825
> 388 2 8 57 137.63322
> 389 2 8 57 132.71925
> 390 2 8 57 131.60252
> 391 2 9 58 141.69515
> 392 2 9 58 140.87751
> 393 2 9 58 137.87803
> 394 2 9 58 136.92587
> 395 2 9 58 142.49341
> 396 2 9 58 137.91539
> 397 2 9 58 143.22549
> 398 2 9 58 141.85922
> 399 2 9 58 142.70592
> 400 2 9 59 134.78737
> 401 2 9 59 134.45188
> 402 2 9 59 135.46179
> 403 2 9 60 139.92808
> 404 2 9 60 135.91592
> 405 2 9 60 138.28296
> 406 2 9 60 138.50250
> 407 2 9 60 141.67469
> 408 2 9 60 136.97090
> 409 2 9 60 137.60102
> 410 2 9 60 137.33454
> 411 2 9 60 138.24363
> 412 2 9 60 138.11670
> 413 2 9 61 138.91641
> 414 2 9 61 141.26137
> 415 2 9 61 141.14156
> 416 2 9 61 141.70831
> 417 2 9 61 139.31144
> 418 2 9 62 138.84849
> 419 2 9 62 141.57434
> 420 2 9 62 139.72705
> 421 2 9 62 141.92184
> 422 2 9 62 142.24466
> 423 2 9 62 142.31485
> 424 2 9 62 139.30274
> 425 2 9 62 140.02032
> 426 2 9 63 142.09815
> 427 2 9 63 135.51280
> 428 2 9 63 135.37869
> 429 2 9 63 136.94111
> 430 2 9 63 137.89716
> 431 2 9 64 139.43889
> 432 2 9 64 143.77447
> 433 2 9 64 138.28852
> 434 2 9 64 144.13810
> 435 2 9 64 142.66261
> 436 2 9 64 143.08367
> 437 2 9 65 138.54363
> 438 2 9 65 138.71649
> 439 2 9 65 138.72531
> 440 2 9 65 141.54971
> 441 2 9 65 141.42357
> 442 2 9 65 139.68311
> 443 2 9 65 136.69522
> 444 2 9 66 138.58361
> 445 2 9 66 141.66582
> 446 2 9 66 141.93508
> 447 2 10 67 141.79622
> 448 2 10 67 140.08933
> 449 2 10 67 141.08196
> 450 2 10 67 139.13432
> 451 2 10 67 139.17769
> 452 2 10 67 140.24739
> 453 2 10 68 137.88723
> 454 2 10 68 136.21334
> 455 2 10 68 134.38966
> 456 2 10 68 138.07545
> 457 2 10 68 134.63247
> 458 2 10 68 138.09769
> 459 2 10 68 138.80486
> 460 2 10 68 136.07520
> 461 2 10 68 137.95119
> 462 2 10 69 135.74640
> 463 2 10 69 135.23309
> 464 2 10 69 138.52815
> 465 2 10 69 137.52413
> 466 2 10 69 135.34352
> 467 2 10 69 139.65881
> 468 2 10 69 136.75848
> 469 2 10 69 137.27209
> 470 2 10 70 138.28514
> 471 2 10 70 133.33658
> 472 2 10 70 139.64858
> 473 2 10 70 136.73697
> 474 2 10 70 138.74611
> 475 2 10 70 135.90308
> 476 2 10 70 140.37966
> 477 2 10 71 132.77171
> 478 2 10 71 131.83492
> 479 2 10 71 133.37638
> 480 2 10 71 136.32626
> 481 2 10 71 134.18070
> 482 2 10 71 133.40606
> 483 2 10 72 136.23553
> 484 2 10 72 136.88210
> 485 2 10 72 138.08141
> 486 2 10 73 133.72177
> 487 2 10 73 132.46714
> 488 2 10 73 131.67315
> 489 2 10 73 130.40442
> 490 2 10 73 136.05875
> 491 2 10 73 131.12366
> 492 2 11 74 136.83976
> 493 2 11 74 137.65805
> 494 2 11 74 138.83342
> 495 2 11 74 138.41757
> 496 2 11 74 137.67666
> 497 2 11 74 137.02564
> 498 2 11 74 137.68975
> 499 2 11 74 139.70267
> 500 2 11 75 133.91438
> 501 2 11 75 137.05986
> 502 2 11 75 133.80643
> 503 2 11 76 134.13757
> 504 2 11 76 137.80003
> 505 2 11 76 134.40863
> 506 2 11 77 133.71111
> 507 2 11 77 132.54085
> 508 2 11 77 135.61060
> 509 2 11 77 137.84123
> 510 2 11 77 136.63525
> 511 2 11 77 135.67345
> 512 2 11 77 131.61030
> 513 2 11 77 137.24940
> 514 2 11 77 136.14587
> 515 2 11 77 132.75982
> 516 2 11 78 133.66413
> 517 2 11 78 129.23438
> 518 2 11 78 130.66778
> 519 2 11 78 131.74449
> 520 2 11 78 127.99984
> 521 2 11 78 130.85677
> 522 2 11 78 132.29773
> 523 2 11 78 125.90397
> 524 2 11 79 132.36451
> 525 2 11 79 131.41107
> 526 2 11 79 135.50790
> 527 2 11 79 132.49138
> 528 2 11 79 132.05823
> 529 2 11 80 131.83975
> 530 2 11 80 132.43526
> 531 2 11 80 132.68158
> 532 2 11 80 130.83804
> 533 2 11 80 130.63738
> 534 2 11 80 132.71383
> 535 2 11 80 134.35993
> 536 2 11 80 129.34706
> 537 2 12 81 135.38196
> 538 2 12 81 136.51656
> 539 2 12 81 142.13254
> 540 2 12 81 136.13347
> 541 2 12 81 138.95599
> 542 2 12 81 137.78775
> 543 2 12 81 137.44595
> 544 2 12 81 141.31883
> 545 2 12 82 142.11169
> 546 2 12 82 138.40488
> 547 2 12 82 137.75370
> 548 2 12 82 137.76209
> 549 2 12 83 136.63206
> 550 2 12 83 136.65165
> 551 2 12 83 131.40959
> 552 2 12 83 132.14400
> 553 2 12 84 138.54710
> 554 2 12 84 137.35134
> 555 2 12 84 136.73340
> 556 2 12 85 136.45393
> 557 2 12 85 139.60750
> 558 2 12 85 138.19983
> 559 2 12 85 137.19454
> 560 2 12 85 138.87344
> 561 2 12 85 137.45111
> 562 2 12 85 138.13030
> 563 2 12 85 142.53493
> 564 2 12 86 145.72187
> 565 2 12 86 139.65313
> 566 2 12 86 143.64877
> 567 2 12 86 141.55768
> 568 2 12 87 140.12291
> 569 2 12 87 140.26232
> 570 2 12 87 138.80004
> 571 2 12 87 143.59403
> 572 2 12 87 140.22496
> 573 2 12 87 139.68820
> 574 2 12 87 141.12759
> 575 2 12 87 138.24798
> 576 2 12 88 134.81386
> 577 2 12 88 139.21436
> 578 2 12 88 143.13216
> 579 2 12 88 134.17893
> 580 2 12 88 136.58512
> 581 2 12 88 136.81961
> 582 2 12 88 137.66847
> 583 2 12 88 142.04899
> 584 2 12 88 143.23715
> 585 2 12 89 140.39384
> 586 2 12 89 133.12719
> 587 2 12 89 140.97148
> 588 2 12 89 143.71183
> 589 2 12 89 141.01992
> 590 2 12 89 139.26778
> 591 2 12 89 138.81498
> 592 2 12 89 140.62789
> 593 2 12 89 135.35761
> 594 3 13 90 84.11477
> 595 3 13 90 82.43232
> 596 3 13 90 84.75199
> 597 3 13 90 83.38023
> 598 3 13 90 86.87028
> 599 3 13 91 89.26388
> 600 3 13 91 86.29747
> 601 3 13 91 91.96651
> 602 3 13 91 89.31114
> 603 3 13 92 89.95994
> 604 3 13 92 88.00278
> 605 3 13 92 87.76271
> 606 3 13 92 88.75470
> 607 3 13 92 86.37940
> 608 3 13 92 83.41832
> 609 3 13 93 87.19313
> 610 3 13 93 88.31828
> 611 3 13 93 90.75864
> 612 3 13 93 84.20821
> 613 3 13 93 85.31005
> 614 3 13 93 86.93236
> 615 3 13 93 87.86621
> 616 3 13 94 85.25960
> 617 3 13 94 88.68357
> 618 3 13 94 86.15820
> 619 3 13 94 89.32044
> 620 3 13 94 89.02343
> 621 3 13 94 89.73263
> 622 3 13 95 85.26636
> 623 3 13 95 84.44676
> 624 3 13 95 84.97538
> 625 3 13 95 84.36085
> 626 3 13 95 88.68830
> 627 3 13 95 83.19141
> 628 3 13 95 88.42778
> 629 3 13 95 82.23288
> 630 3 13 95 85.82567
> 631 3 13 95 82.99967
> 632 3 13 96 86.36148
> 633 3 13 96 89.93701
> 634 3 13 96 87.96666
> 635 3 13 96 92.90167
> 636 3 13 96 88.17896
> 637 3 13 96 88.42843
> 638 3 13 96 86.59386
> 639 3 13 96 88.92571
> 640 3 13 96 89.65149
> 641 3 13 97 80.69288
> 642 3 13 97 80.51843
> 643 3 13 97 80.65669
> 644 3 13 97 84.63768
> 645 3 13 97 83.11279
> 646 3 13 97 85.42411
> 647 3 13 98 92.89441
> 648 3 13 98 88.13733
> 649 3 13 98 93.12429
> 650 3 13 98 92.47392
> 651 3 13 98 90.59924
> 652 3 13 98 91.95135
> 653 3 13 98 92.09058
> 654 3 13 98 89.52612
> 655 3 13 98 87.88851
> 656 3 14 99 89.02332
> 657 3 14 99 85.62671
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> 1334 4 27 203 76.81514
> 1335 4 27 203 76.37141
> 1336 4 27 203 73.72629
> 1337 4 27 203 73.96121
> 1338 4 27 203 76.48921
> 1339 4 27 203 73.62458
> 1340 4 27 203 79.62571
> 1341 4 27 203 78.85458
> 1342 4 28 204 74.77381
> 1343 4 28 204 76.23763
> 1344 4 28 204 72.47837
> 1345 4 28 204 78.03019
> 1346 4 28 204 82.21757
> 1347 4 28 204 77.18483
> 1348 4 28 205 71.63301
> 1349 4 28 205 75.79059
> 1350 4 28 205 72.64033
> 1351 4 28 205 74.93365
> 1352 4 28 205 75.28804
> 1353 4 28 205 74.93150
> 1354 4 28 205 76.58337
> 1355 4 28 205 73.85332
> 1356 4 28 205 74.62220
> 1357 4 28 206 74.36743
> 1358 4 28 206 74.88352
> 1359 4 28 206 73.62345
> 1360 4 28 206 77.68120
> 1361 4 28 206 75.90436
> 1362 4 28 206 79.31979
> 1363 4 28 206 77.67978
> 1364 4 28 206 78.43844
> 1365 4 28 206 76.94857
> 1366 4 28 207 78.08868
> 1367 4 28 207 78.84407
> 1368 4 28 207 75.26613
> 1369 4 28 207 78.58939
> 1370 4 28 207 76.84015
> 1371 4 28 207 76.21987
> 1372 4 28 207 75.92112
> 1373 4 28 208 74.16221
> 1374 4 28 208 71.56339
> 1375 4 28 208 70.96351
> 1376 4 28 208 70.15148
> 1377 4 28 208 71.22260
> 1378 4 28 209 81.53390
> 1379 4 28 209 76.92364
> 1380 4 28 209 76.20069
> 1381 4 28 210 77.11346
> 1382 4 28 210 77.65432
> 1383 4 28 210 76.03240
> 1384 4 28 210 79.51629
> 1385 4 28 210 80.29334
> 1386 4 28 210 80.09958
> 1387 4 28 210 83.26490
> 1388 4 28 210 78.21371
> 1389 4 28 210 78.89779
> 1390 4 28 211 75.96139
> 1391 4 28 211 75.22922
> 1392 4 28 211 77.70700
> 1393 4 28 211 78.91582
> 1394 4 28 211 75.91998
> 1395 4 28 212 73.80985
> 1396 4 28 212 76.88150
> 1397 4 28 212 77.74419
> 1398 4 28 212 75.18593Code
# trt type id milesone pre post (1:2,1:2,1:41,1:16)
# patients 41 , 16 milestoes asign trt assign type
#
# id=1;
# miles=16
#
# mat <- matrix(nrow=16*41, ncol=2)
#
# mat
#
#
# #use nested for loop to fill in values of matrix
# for(i in 1:41) {
# for(j in 1:41*16) {
# k = i*j
# mat[i, 1] = k
# mat[j, 2] = j
# }
# }R Packages Used
Code
# For session info and package reporting
library("report")
# For reading files
library("readr")
# For interactive tables
library("reactable")
library("htmltools")
# For data wrangling
library("dplyr")
library("tidyr")
library("tibble")
library("purrr")
library("broom")
library("glue")
# For palatte colours
library("scales")
# For lipid annotation
# Install from BioConductor
library("rgoslin")
# For plotting
library("plotly")
# For cognostics
library("assertable")
# For combining plotly plots
library("manipulateWidget")
# For trellis plot
library("trelliscopejs")
sessionInfo() |>
report::report() |>
summary()The analysis was done using the R Statistical language (v4.2.1; R Core Team, 2022) on Windows 10 x64, using the packages manipulateWidget (v0.11.1), htmltools (v0.5.3), trelliscopejs (v0.2.6), purrr (v0.3.5), glue (v1.6.2), rgoslin (v1.0.0), reactable (v0.3.0), report (v0.5.5), tibble (v3.1.8), assertable (v0.2.8), broom (v1.0.1), plotly (v4.10.0), ggplot2 (v3.3.6), dplyr (v1.0.10), tidyr (v1.2.1), readr (v2.1.3) and scales (v1.2.1).
Input Data
The data we are using are from Wolrab et. al 2022 [@Wolrab2022].
xxxxx xxxxxxxxxxx.
The first column is the name of the sample. Subsequent columns are the transition’s integrated peak areas.
A docs folder will be created. It is currently placed in this GitHub repository.
Below is just an embedded webpage of the trellis plot. It can be accessed via this GitHub Page link.
Package References
Code
get_citation <- function(package_name) {
transform_name <- package_name |>
citation() |>
format(style="text")
return(transform_name)
}
packages <- c("base","here", "readr", "reactable",
"htmltools", "dplyr", "tidyr", "tibble",
"broom", "glue", "purrr", "scales",
"rgoslin", "plotly", "assertable",
"manipulateWidget", "trelliscopejs",
"report")
table <- tibble::tibble(Packages = packages)References
Citation
BibTeX citation:
@online{jojo2022,
author = {jojo},
title = {Quarto {Report} {Example}},
date = {2022-08-08},
url = {https://www.google.com/},
langid = {en},
abstract = {A report showing how to xxxxxxxxxxxxxxxxxxxxxxxxxxxxx.}
}
For attribution, please cite this work as:
jojo. 2022. “Quarto Report Example.” August 8, 2022. https://www.google.com/.