Chapter 20 Randomization for Clinical Trials with R

There are a number of packages for doing key functions for clinical trials in R. You can find many of these on the CRAN Task View for Clinical Trials, at https://cran.r-project.org/web/views/ClinicalTrials.html.

This is a curated list of packages that anyone might find useful in designing, monitoring, or analyzing clinical trials, and is often a good place to start in looking for packages that might be relevant for clinical trials.

If you use Ctrl-F to search the web page for “rand”, several packages address randomization, including

  • blockrand

  • randomizeR

  • pwr

  • experiment

  • clusterPower

  • CRTSize

  • cosa

  • PowerupR

Several of these are specifically for more complex designs, including cluster and multilevel randomization (clusterPower, cosa, CRTSize). For today, we will focus on the straightforward randomization packages including {blockrand} and {randomizer}. The {blockrand} package creates randomizations for clinical trials with can include stratified enrollment and permuted block randomization, and can produce a PDF file of randomization cards.

Let’s start with an example in {blockrand}.

Details on the package can be found at https://cran.r-project.org/web/packages/blockrand/blockrand.pdf

or by running help(blockrand) in your Console.

You want to randomize 180 inpatients with severe ulcerative colitis to one of 3 arms: corticosteroids alone (control), corticosteroids + tofacitinib, or corticosteroids + upadacitinib. You want to stratify the participants by (1) prior biologic failure and (2) Albumin level above or below 3.0. To be prepared for dropouts and imbalanced enrollment, you want to have a randomization list with at least 60 assignments available for each arm and stratum. To avoid a recognizable pattern in the randomization, you want to have a permuted block design with blocks of sizes 3, 6, and 9.
Below, you will see how to do this for the biologic failure - low albumin stratum.

bfla <- blockrand(n = 60, 
                     num.levels = 3, # three treatments
                     levels = c("CS", "CS/Tofa", "CS/Upa"), # arm names
                     stratum = "Bfail.LowAlb", # stratum name
                     id.prefix = "BfLA", # stratum abbrev
                     block.sizes = c(1,2,3), # times arms = 3,6,9
                     block.prefix = "BfLA") # stratum abbrev
bfla
##        id      stratum block.id block.size treatment
## 1  BfLA01 Bfail.LowAlb   BfLA01          9    CS/Upa
## 2  BfLA02 Bfail.LowAlb   BfLA01          9   CS/Tofa
## 3  BfLA03 Bfail.LowAlb   BfLA01          9    CS/Upa
## 4  BfLA04 Bfail.LowAlb   BfLA01          9        CS
## 5  BfLA05 Bfail.LowAlb   BfLA01          9    CS/Upa
## 6  BfLA06 Bfail.LowAlb   BfLA01          9        CS
## 7  BfLA07 Bfail.LowAlb   BfLA01          9        CS
## 8  BfLA08 Bfail.LowAlb   BfLA01          9   CS/Tofa
## 9  BfLA09 Bfail.LowAlb   BfLA01          9   CS/Tofa
## 10 BfLA10 Bfail.LowAlb   BfLA02          6    CS/Upa
## 11 BfLA11 Bfail.LowAlb   BfLA02          6        CS
## 12 BfLA12 Bfail.LowAlb   BfLA02          6    CS/Upa
## 13 BfLA13 Bfail.LowAlb   BfLA02          6   CS/Tofa
## 14 BfLA14 Bfail.LowAlb   BfLA02          6        CS
## 15 BfLA15 Bfail.LowAlb   BfLA02          6   CS/Tofa
## 16 BfLA16 Bfail.LowAlb   BfLA03          3   CS/Tofa
## 17 BfLA17 Bfail.LowAlb   BfLA03          3        CS
## 18 BfLA18 Bfail.LowAlb   BfLA03          3    CS/Upa
## 19 BfLA19 Bfail.LowAlb   BfLA04          6        CS
## 20 BfLA20 Bfail.LowAlb   BfLA04          6    CS/Upa
## 21 BfLA21 Bfail.LowAlb   BfLA04          6   CS/Tofa
## 22 BfLA22 Bfail.LowAlb   BfLA04          6   CS/Tofa
## 23 BfLA23 Bfail.LowAlb   BfLA04          6    CS/Upa
## 24 BfLA24 Bfail.LowAlb   BfLA04          6        CS
## 25 BfLA25 Bfail.LowAlb   BfLA05          9   CS/Tofa
## 26 BfLA26 Bfail.LowAlb   BfLA05          9        CS
## 27 BfLA27 Bfail.LowAlb   BfLA05          9    CS/Upa
## 28 BfLA28 Bfail.LowAlb   BfLA05          9        CS
## 29 BfLA29 Bfail.LowAlb   BfLA05          9   CS/Tofa
## 30 BfLA30 Bfail.LowAlb   BfLA05          9   CS/Tofa
## 31 BfLA31 Bfail.LowAlb   BfLA05          9    CS/Upa
## 32 BfLA32 Bfail.LowAlb   BfLA05          9    CS/Upa
## 33 BfLA33 Bfail.LowAlb   BfLA05          9        CS
## 34 BfLA34 Bfail.LowAlb   BfLA06          6   CS/Tofa
## 35 BfLA35 Bfail.LowAlb   BfLA06          6    CS/Upa
## 36 BfLA36 Bfail.LowAlb   BfLA06          6        CS
## 37 BfLA37 Bfail.LowAlb   BfLA06          6    CS/Upa
## 38 BfLA38 Bfail.LowAlb   BfLA06          6        CS
## 39 BfLA39 Bfail.LowAlb   BfLA06          6   CS/Tofa
## 40 BfLA40 Bfail.LowAlb   BfLA07          3    CS/Upa
## 41 BfLA41 Bfail.LowAlb   BfLA07          3        CS
## 42 BfLA42 Bfail.LowAlb   BfLA07          3   CS/Tofa
## 43 BfLA43 Bfail.LowAlb   BfLA08          6    CS/Upa
## 44 BfLA44 Bfail.LowAlb   BfLA08          6   CS/Tofa
## 45 BfLA45 Bfail.LowAlb   BfLA08          6        CS
## 46 BfLA46 Bfail.LowAlb   BfLA08          6        CS
## 47 BfLA47 Bfail.LowAlb   BfLA08          6   CS/Tofa
## 48 BfLA48 Bfail.LowAlb   BfLA08          6    CS/Upa
## 49 BfLA49 Bfail.LowAlb   BfLA09          9        CS
## 50 BfLA50 Bfail.LowAlb   BfLA09          9   CS/Tofa
## 51 BfLA51 Bfail.LowAlb   BfLA09          9   CS/Tofa
## 52 BfLA52 Bfail.LowAlb   BfLA09          9   CS/Tofa
## 53 BfLA53 Bfail.LowAlb   BfLA09          9    CS/Upa
## 54 BfLA54 Bfail.LowAlb   BfLA09          9    CS/Upa
## 55 BfLA55 Bfail.LowAlb   BfLA09          9        CS
## 56 BfLA56 Bfail.LowAlb   BfLA09          9    CS/Upa
## 57 BfLA57 Bfail.LowAlb   BfLA09          9        CS
## 58 BfLA58 Bfail.LowAlb   BfLA10          6        CS
## 59 BfLA59 Bfail.LowAlb   BfLA10          6        CS
## 60 BfLA60 Bfail.LowAlb   BfLA10          6    CS/Upa
## 61 BfLA61 Bfail.LowAlb   BfLA10          6   CS/Tofa
## 62 BfLA62 Bfail.LowAlb   BfLA10          6   CS/Tofa
## 63 BfLA63 Bfail.LowAlb   BfLA10          6    CS/Upa

You can see the id for each participant, their stratum, the block.id for their permuted block, the block.size, and their assigned treatment. You can imagine this as a randomization list, or as assignments that you could print out on cards and seal in security envelopes for the time of randomization. Of course, this is only one of our four strata. We should do the same for the 3 other strata.

bfha <- blockrand(n = 60, 
                     num.levels = 3, # three treatments
                     levels = c("CS", "CS/Tofa", "CS/Upa"), # arm names
                     stratum = "Bfail.HiAlb", # stratum name
                     id.prefix = "BfHA", # stratum abbrev
                     block.sizes = c(1,2,3), # times arms = 3,6,9
                     block.prefix = "BfHA") # stratum abbrev
bfha
##        id     stratum block.id block.size treatment
## 1  BfHA01 Bfail.HiAlb    BfHA1          9   CS/Tofa
## 2  BfHA02 Bfail.HiAlb    BfHA1          9        CS
## 3  BfHA03 Bfail.HiAlb    BfHA1          9    CS/Upa
## 4  BfHA04 Bfail.HiAlb    BfHA1          9        CS
## 5  BfHA05 Bfail.HiAlb    BfHA1          9    CS/Upa
## 6  BfHA06 Bfail.HiAlb    BfHA1          9   CS/Tofa
## 7  BfHA07 Bfail.HiAlb    BfHA1          9    CS/Upa
## 8  BfHA08 Bfail.HiAlb    BfHA1          9   CS/Tofa
## 9  BfHA09 Bfail.HiAlb    BfHA1          9        CS
## 10 BfHA10 Bfail.HiAlb    BfHA2          6    CS/Upa
## 11 BfHA11 Bfail.HiAlb    BfHA2          6    CS/Upa
## 12 BfHA12 Bfail.HiAlb    BfHA2          6        CS
## 13 BfHA13 Bfail.HiAlb    BfHA2          6        CS
## 14 BfHA14 Bfail.HiAlb    BfHA2          6   CS/Tofa
## 15 BfHA15 Bfail.HiAlb    BfHA2          6   CS/Tofa
## 16 BfHA16 Bfail.HiAlb    BfHA3          9        CS
## 17 BfHA17 Bfail.HiAlb    BfHA3          9   CS/Tofa
## 18 BfHA18 Bfail.HiAlb    BfHA3          9    CS/Upa
## 19 BfHA19 Bfail.HiAlb    BfHA3          9   CS/Tofa
## 20 BfHA20 Bfail.HiAlb    BfHA3          9        CS
## 21 BfHA21 Bfail.HiAlb    BfHA3          9    CS/Upa
## 22 BfHA22 Bfail.HiAlb    BfHA3          9        CS
## 23 BfHA23 Bfail.HiAlb    BfHA3          9   CS/Tofa
## 24 BfHA24 Bfail.HiAlb    BfHA3          9    CS/Upa
## 25 BfHA25 Bfail.HiAlb    BfHA4          9   CS/Tofa
## 26 BfHA26 Bfail.HiAlb    BfHA4          9    CS/Upa
## 27 BfHA27 Bfail.HiAlb    BfHA4          9        CS
## 28 BfHA28 Bfail.HiAlb    BfHA4          9    CS/Upa
## 29 BfHA29 Bfail.HiAlb    BfHA4          9   CS/Tofa
## 30 BfHA30 Bfail.HiAlb    BfHA4          9    CS/Upa
## 31 BfHA31 Bfail.HiAlb    BfHA4          9        CS
## 32 BfHA32 Bfail.HiAlb    BfHA4          9        CS
## 33 BfHA33 Bfail.HiAlb    BfHA4          9   CS/Tofa
## 34 BfHA34 Bfail.HiAlb    BfHA5          3    CS/Upa
## 35 BfHA35 Bfail.HiAlb    BfHA5          3        CS
## 36 BfHA36 Bfail.HiAlb    BfHA5          3   CS/Tofa
## 37 BfHA37 Bfail.HiAlb    BfHA6          9        CS
## 38 BfHA38 Bfail.HiAlb    BfHA6          9        CS
## 39 BfHA39 Bfail.HiAlb    BfHA6          9   CS/Tofa
## 40 BfHA40 Bfail.HiAlb    BfHA6          9    CS/Upa
## 41 BfHA41 Bfail.HiAlb    BfHA6          9    CS/Upa
## 42 BfHA42 Bfail.HiAlb    BfHA6          9        CS
## 43 BfHA43 Bfail.HiAlb    BfHA6          9   CS/Tofa
## 44 BfHA44 Bfail.HiAlb    BfHA6          9    CS/Upa
## 45 BfHA45 Bfail.HiAlb    BfHA6          9   CS/Tofa
## 46 BfHA46 Bfail.HiAlb    BfHA7          6   CS/Tofa
## 47 BfHA47 Bfail.HiAlb    BfHA7          6        CS
## 48 BfHA48 Bfail.HiAlb    BfHA7          6        CS
## 49 BfHA49 Bfail.HiAlb    BfHA7          6   CS/Tofa
## 50 BfHA50 Bfail.HiAlb    BfHA7          6    CS/Upa
## 51 BfHA51 Bfail.HiAlb    BfHA7          6    CS/Upa
## 52 BfHA52 Bfail.HiAlb    BfHA8          9        CS
## 53 BfHA53 Bfail.HiAlb    BfHA8          9   CS/Tofa
## 54 BfHA54 Bfail.HiAlb    BfHA8          9        CS
## 55 BfHA55 Bfail.HiAlb    BfHA8          9   CS/Tofa
## 56 BfHA56 Bfail.HiAlb    BfHA8          9    CS/Upa
## 57 BfHA57 Bfail.HiAlb    BfHA8          9   CS/Tofa
## 58 BfHA58 Bfail.HiAlb    BfHA8          9    CS/Upa
## 59 BfHA59 Bfail.HiAlb    BfHA8          9    CS/Upa
## 60 BfHA60 Bfail.HiAlb    BfHA8          9        CS
bnha <- blockrand(n = 60, 
                     num.levels = 3, 
                     levels = c("CS", "CS/Tofa", "CS/Upa"),
                     stratum = "Bnaive.HiAlb",
                     id.prefix = "BnHA",
                     block.sizes = c(1,2,3, 4), 
                     block.prefix = "BnHA")
bnha
##        id      stratum block.id block.size treatment
## 1  BnHA01 Bnaive.HiAlb    BnHA1         12    CS/Upa
## 2  BnHA02 Bnaive.HiAlb    BnHA1         12   CS/Tofa
## 3  BnHA03 Bnaive.HiAlb    BnHA1         12        CS
## 4  BnHA04 Bnaive.HiAlb    BnHA1         12   CS/Tofa
## 5  BnHA05 Bnaive.HiAlb    BnHA1         12   CS/Tofa
## 6  BnHA06 Bnaive.HiAlb    BnHA1         12        CS
## 7  BnHA07 Bnaive.HiAlb    BnHA1         12        CS
## 8  BnHA08 Bnaive.HiAlb    BnHA1         12    CS/Upa
## 9  BnHA09 Bnaive.HiAlb    BnHA1         12    CS/Upa
## 10 BnHA10 Bnaive.HiAlb    BnHA1         12    CS/Upa
## 11 BnHA11 Bnaive.HiAlb    BnHA1         12        CS
## 12 BnHA12 Bnaive.HiAlb    BnHA1         12   CS/Tofa
## 13 BnHA13 Bnaive.HiAlb    BnHA2         12    CS/Upa
## 14 BnHA14 Bnaive.HiAlb    BnHA2         12   CS/Tofa
## 15 BnHA15 Bnaive.HiAlb    BnHA2         12        CS
## 16 BnHA16 Bnaive.HiAlb    BnHA2         12   CS/Tofa
## 17 BnHA17 Bnaive.HiAlb    BnHA2         12   CS/Tofa
## 18 BnHA18 Bnaive.HiAlb    BnHA2         12   CS/Tofa
## 19 BnHA19 Bnaive.HiAlb    BnHA2         12    CS/Upa
## 20 BnHA20 Bnaive.HiAlb    BnHA2         12    CS/Upa
## 21 BnHA21 Bnaive.HiAlb    BnHA2         12        CS
## 22 BnHA22 Bnaive.HiAlb    BnHA2         12    CS/Upa
## 23 BnHA23 Bnaive.HiAlb    BnHA2         12        CS
## 24 BnHA24 Bnaive.HiAlb    BnHA2         12        CS
## 25 BnHA25 Bnaive.HiAlb    BnHA3          6   CS/Tofa
## 26 BnHA26 Bnaive.HiAlb    BnHA3          6   CS/Tofa
## 27 BnHA27 Bnaive.HiAlb    BnHA3          6    CS/Upa
## 28 BnHA28 Bnaive.HiAlb    BnHA3          6        CS
## 29 BnHA29 Bnaive.HiAlb    BnHA3          6        CS
## 30 BnHA30 Bnaive.HiAlb    BnHA3          6    CS/Upa
## 31 BnHA31 Bnaive.HiAlb    BnHA4          6    CS/Upa
## 32 BnHA32 Bnaive.HiAlb    BnHA4          6        CS
## 33 BnHA33 Bnaive.HiAlb    BnHA4          6        CS
## 34 BnHA34 Bnaive.HiAlb    BnHA4          6   CS/Tofa
## 35 BnHA35 Bnaive.HiAlb    BnHA4          6    CS/Upa
## 36 BnHA36 Bnaive.HiAlb    BnHA4          6   CS/Tofa
## 37 BnHA37 Bnaive.HiAlb    BnHA5         12   CS/Tofa
## 38 BnHA38 Bnaive.HiAlb    BnHA5         12    CS/Upa
## 39 BnHA39 Bnaive.HiAlb    BnHA5         12        CS
## 40 BnHA40 Bnaive.HiAlb    BnHA5         12    CS/Upa
## 41 BnHA41 Bnaive.HiAlb    BnHA5         12    CS/Upa
## 42 BnHA42 Bnaive.HiAlb    BnHA5         12    CS/Upa
## 43 BnHA43 Bnaive.HiAlb    BnHA5         12        CS
## 44 BnHA44 Bnaive.HiAlb    BnHA5         12   CS/Tofa
## 45 BnHA45 Bnaive.HiAlb    BnHA5         12   CS/Tofa
## 46 BnHA46 Bnaive.HiAlb    BnHA5         12   CS/Tofa
## 47 BnHA47 Bnaive.HiAlb    BnHA5         12        CS
## 48 BnHA48 Bnaive.HiAlb    BnHA5         12        CS
## 49 BnHA49 Bnaive.HiAlb    BnHA6         12        CS
## 50 BnHA50 Bnaive.HiAlb    BnHA6         12    CS/Upa
## 51 BnHA51 Bnaive.HiAlb    BnHA6         12    CS/Upa
## 52 BnHA52 Bnaive.HiAlb    BnHA6         12   CS/Tofa
## 53 BnHA53 Bnaive.HiAlb    BnHA6         12    CS/Upa
## 54 BnHA54 Bnaive.HiAlb    BnHA6         12   CS/Tofa
## 55 BnHA55 Bnaive.HiAlb    BnHA6         12        CS
## 56 BnHA56 Bnaive.HiAlb    BnHA6         12        CS
## 57 BnHA57 Bnaive.HiAlb    BnHA6         12        CS
## 58 BnHA58 Bnaive.HiAlb    BnHA6         12    CS/Upa
## 59 BnHA59 Bnaive.HiAlb    BnHA6         12   CS/Tofa
## 60 BnHA60 Bnaive.HiAlb    BnHA6         12   CS/Tofa
bnla <- blockrand(n = 60, 
                     num.levels = 3, 
                     levels = c("CS", "CS/Tofa", "CS/Upa"),
                     stratum = "Bnaive.LoAlb",
                     id.prefix = "BnLA",
                     block.sizes = c(1,2,3), 
                     block.prefix = "BnLA")
bnla
##        id      stratum block.id block.size treatment
## 1  BnLA01 Bnaive.LoAlb   BnLA01          6   CS/Tofa
## 2  BnLA02 Bnaive.LoAlb   BnLA01          6        CS
## 3  BnLA03 Bnaive.LoAlb   BnLA01          6   CS/Tofa
## 4  BnLA04 Bnaive.LoAlb   BnLA01          6    CS/Upa
## 5  BnLA05 Bnaive.LoAlb   BnLA01          6    CS/Upa
## 6  BnLA06 Bnaive.LoAlb   BnLA01          6        CS
## 7  BnLA07 Bnaive.LoAlb   BnLA02          9    CS/Upa
## 8  BnLA08 Bnaive.LoAlb   BnLA02          9   CS/Tofa
## 9  BnLA09 Bnaive.LoAlb   BnLA02          9   CS/Tofa
## 10 BnLA10 Bnaive.LoAlb   BnLA02          9        CS
## 11 BnLA11 Bnaive.LoAlb   BnLA02          9    CS/Upa
## 12 BnLA12 Bnaive.LoAlb   BnLA02          9        CS
## 13 BnLA13 Bnaive.LoAlb   BnLA02          9        CS
## 14 BnLA14 Bnaive.LoAlb   BnLA02          9   CS/Tofa
## 15 BnLA15 Bnaive.LoAlb   BnLA02          9    CS/Upa
## 16 BnLA16 Bnaive.LoAlb   BnLA03          9    CS/Upa
## 17 BnLA17 Bnaive.LoAlb   BnLA03          9   CS/Tofa
## 18 BnLA18 Bnaive.LoAlb   BnLA03          9        CS
## 19 BnLA19 Bnaive.LoAlb   BnLA03          9   CS/Tofa
## 20 BnLA20 Bnaive.LoAlb   BnLA03          9    CS/Upa
## 21 BnLA21 Bnaive.LoAlb   BnLA03          9        CS
## 22 BnLA22 Bnaive.LoAlb   BnLA03          9        CS
## 23 BnLA23 Bnaive.LoAlb   BnLA03          9   CS/Tofa
## 24 BnLA24 Bnaive.LoAlb   BnLA03          9    CS/Upa
## 25 BnLA25 Bnaive.LoAlb   BnLA04          3    CS/Upa
## 26 BnLA26 Bnaive.LoAlb   BnLA04          3        CS
## 27 BnLA27 Bnaive.LoAlb   BnLA04          3   CS/Tofa
## 28 BnLA28 Bnaive.LoAlb   BnLA05          3   CS/Tofa
## 29 BnLA29 Bnaive.LoAlb   BnLA05          3        CS
## 30 BnLA30 Bnaive.LoAlb   BnLA05          3    CS/Upa
## 31 BnLA31 Bnaive.LoAlb   BnLA06          6   CS/Tofa
## 32 BnLA32 Bnaive.LoAlb   BnLA06          6    CS/Upa
## 33 BnLA33 Bnaive.LoAlb   BnLA06          6        CS
## 34 BnLA34 Bnaive.LoAlb   BnLA06          6   CS/Tofa
## 35 BnLA35 Bnaive.LoAlb   BnLA06          6        CS
## 36 BnLA36 Bnaive.LoAlb   BnLA06          6    CS/Upa
## 37 BnLA37 Bnaive.LoAlb   BnLA07          6        CS
## 38 BnLA38 Bnaive.LoAlb   BnLA07          6    CS/Upa
## 39 BnLA39 Bnaive.LoAlb   BnLA07          6    CS/Upa
## 40 BnLA40 Bnaive.LoAlb   BnLA07          6   CS/Tofa
## 41 BnLA41 Bnaive.LoAlb   BnLA07          6        CS
## 42 BnLA42 Bnaive.LoAlb   BnLA07          6   CS/Tofa
## 43 BnLA43 Bnaive.LoAlb   BnLA08          9        CS
## 44 BnLA44 Bnaive.LoAlb   BnLA08          9   CS/Tofa
## 45 BnLA45 Bnaive.LoAlb   BnLA08          9    CS/Upa
## 46 BnLA46 Bnaive.LoAlb   BnLA08          9        CS
## 47 BnLA47 Bnaive.LoAlb   BnLA08          9   CS/Tofa
## 48 BnLA48 Bnaive.LoAlb   BnLA08          9    CS/Upa
## 49 BnLA49 Bnaive.LoAlb   BnLA08          9        CS
## 50 BnLA50 Bnaive.LoAlb   BnLA08          9    CS/Upa
## 51 BnLA51 Bnaive.LoAlb   BnLA08          9   CS/Tofa
## 52 BnLA52 Bnaive.LoAlb   BnLA09          3   CS/Tofa
## 53 BnLA53 Bnaive.LoAlb   BnLA09          3    CS/Upa
## 54 BnLA54 Bnaive.LoAlb   BnLA09          3        CS
## 55 BnLA55 Bnaive.LoAlb   BnLA10          6   CS/Tofa
## 56 BnLA56 Bnaive.LoAlb   BnLA10          6    CS/Upa
## 57 BnLA57 Bnaive.LoAlb   BnLA10          6    CS/Upa
## 58 BnLA58 Bnaive.LoAlb   BnLA10          6        CS
## 59 BnLA59 Bnaive.LoAlb   BnLA10          6   CS/Tofa
## 60 BnLA60 Bnaive.LoAlb   BnLA10          6        CS

20.1 Printing these on Cards

Ideally, you will print out each randomization on a card, and seal it in a security envelope, with the outside of the envelope labeled with the id. You can do this with the plotblockrand() function. This function creates a pdf file of randomization cards for printing. These are designed so that the middle text will show in a standard letter sized envelope with a window, and the top text (the assignment) can be folded over to increase security (against anyone trying to peek through the security envelope to guess the assignment).

uc_study <- bind_rows(bfha, bfla, bnha, bnla) # bind together the four strata into one dataframe

blockrand::plotblockrand(uc_study, # input dataframe
                    file = "uc_study.pdf", # output pdf
                    # top hidden text with assignment
      top=list(text=c('My Study','Patient: %ID%','Treatment: %TREAT%'),
                col=c('black','black','red'),font=c(1,1,4)),
      # middle text to show through window of # 10 envelope 
    middle=list(text=c("My Study","Stratum: %STRAT%","Patient: %ID%"),
               col=c('black','blue','orange'),font=c(1,2,3)),
    # bottom text- any instructions to study coordinator
   bottom="Call 123-4567 to report patient entry",
   cut.marks=TRUE) # add cut marks - 4 per page

Open up the file uc_study.pdf in your Files tab to see the output pdf file, with assorted fonts and colors.

Just for fun, change (and then re-run) the

  • text “My Study” to something more interesting

  • change “Patient” to “Participant”

  • change “Treatment” to “Arm” or “Assignment”

  • change some of the colors to standard R colors

  • change some of the fonts (within 1-4)

Sometimes with equal blocks, and clear treatment effects or side effects, nurses or study coordinators can guess the randomization pattern. If you want to get fancy, and make it even harder to guess treatment assignments, you can add one of the unequal blocks options, to make it hard to find patterns in treatment or in side effects. Set uneq.beg = TRUE for an unequal block in the beginning, or uneq.mid = TRUE for an unequal block in the middle.

20.2 Now, try this yourself

You want to randomize 80 outpatients with Crohn’s disease to one of 8 arms, as part of a 2^3 factorial design to increase patient activation. These arms involve using (A,B, C) or not using (a,b,c) 3 intervention components. The 8 arms then become:

  • abc

  • abC

  • aBc

  • aBC

  • Abc

  • AbC

  • ABc

  • ABC

Then we want to stratify the participants by baseline PAM score (a measure of patient activation) with levels of low, medium, and high PAM.

To be prepared for dropouts and imbalanced enrollment, you want to have a randomization list with at least 32 assignments available for each arm and stratum. To avoid a recognizable pattern in the randomization, you want to have a permuted block design with blocks of sizes 8 and 16.

You can hover over top right corner of the code chunk below, and a copy icon will appear - click this to copy the code to your clipboard. You can then paste it into your local version of RStudio, edit it, and run it.

In the code block below, fill in the blanks to complete the code to make a dataframe for the low_pam stratum.

low_pam <- blockrand(n = __, 
                     num.levels = __, #eight treatments
  levels = c("abc", "abC", "aBc", "aBC",
             "Abc", "AbC", "ABc", "ABC"), # arm names
                     stratum = "__", # stratum name
                     id.prefix = "lp", # stratum abbrev
                     block.sizes = c(1,2,3), # times arms 
                     block.prefix = "LP") # stratum abbrev
low_pam

Now that you have one stratum sorted, edit the code block below to create the med_pam and high_pam strata.

med_pam <- blockrand(n = __, 
                     num.levels = __, #eight treatments
  levels = c("abc", "abC", "aBc", "aBC",
             "Abc", "AbC", "ABc", "ABC"), # arm names
                     stratum = "__", # stratum name
                     id.prefix = "__", # stratum abbrev
                     block.sizes = c(__), # times arms 
                     block.prefix = "__") # stratum abbrev
med_pam

high_pam <- blockrand(n = __, 
                     num.levels = __, #eight treatments
  levels = c("abc", "abC", "aBc", "aBC",
             "Abc", "AbC", "ABc", "ABC"), # arm names
                     stratum = "__", # stratum name
                     id.prefix = "__", # stratum abbrev
                     block.sizes = c(__), # times arms 
                     block.prefix = "__") # stratum abbrev
high_pam

Great!

Now try to

  • bind these 3 strata into one dataframe

  • print these as cards to a pdf file

Edit the code chunk below to produce the pdf file

cd_study <- bind_rows(__,__,__) # bind together the 3 strata into one dataframe

blockrand::plotblockrand(__, # input dataframe
                    file = "cd_study.pdf", # output pdf
                    # top hidden text with assignment
      top=list(text=c('CD Study','Patient: %ID%','Treatment: %__%'),
                col=c('orange','blue','red'),font=c(1,1,4)),
      # middle text to show through window of # 10 envelope 
    middle=list(text=c("CD Study","Stratum: %STRAT%","Patient: %__%"),
               col=c('black','red','cadetblue'),font=c(1,2,3)),
    # bottom text- any instructions to study coordinator
   bottom="Call 123-4567 to report patient entry",
   cut.marks=TRUE) # add cut marks - 4 per page

20.3 Now Freestyle

Your turn. Create randomization tables and a pdf file of cards for a study of 2 microbiome interventions to reduce the formation of colon adenomas.

  • your 3 study arms will be - placebo, Streptococcus thermophilus, and S.thermo plus lactose (a preferred sugar for S.t, making this arm a synbiotic, while arm 2 is a probiotic) - aka 3 arms called: pbo, probiotic, synbiotic.

  • Your stratifications will be by

    • prior polyps being MSI_hi or MSI_lo (for microsatellite instability mutations)

    • BMI above or below 35. BMI_hi, BMI_low

  • block sizes of 4,8,12,16

  • 160 per arm

Edit the code block below for the first stratum

mhbh <- blockrand(n = __, # treatment arms
                     num.levels = __, # of treatments
  levels = c("placebo", "probiotic", "synbiotic"), # arm names
                     stratum = "__,__", # stratum name
                     id.prefix = "mhbh", # stratum abbrev
                     block.sizes = c(__,__,__,__), # times arms 
                     block.prefix = "__") # stratum abbrev
mhbh

Edit the code block below for the remaining strata

mhbl <- blockrand(n = __, # treatment arms
                     num.levels = 3, # of treatments
  levels = c("placebo", "probiotic", "__"), # arm names
                     stratum = "msi_hi.bmi_lo", # stratum name
                     id.prefix = "__", # stratum abbrev
                     block.sizes = c(1,2,__,__), # times arms 
                     block.prefix = "MHBL") # stratum abbrev
mhbl

mlbl <- blockrand(n = 160, # treatment arms
                     num.levels = __, # of treatments
  levels = c("placebo", "__", "synbiotic"), # arm names
                     stratum = "__", # stratum name
                     id.prefix = "mlbl", # stratum abbrev
                     block.sizes = c(__,__,3,4), # times arms 
                     block.prefix = "MLBL") # stratum abbrev
mlbl

mlbh <- blockrand(n = __, # treatment arms
                     num.levels = 3, # of treatments
  levels = c("__", "probiotic", "synbiotic"), # arm names
                     stratum = "msi_lo.bmi_hi", # stratum name
                     id.prefix = "__", # stratum abbrev
                     block.sizes = c(1,2,3,4), # times arms 
                     block.prefix = "MLBH") # stratum abbrev
mlbh

Edit the code block below to bind the strata together and print the cards

adenoma_study <- bind_rows(mlbl, mlbh, mhbh, mhbl) # bind together the strata into one dataframe

blockrand::plotblockrand(__, # input dataframe
                    file = "adenoma_cards.pdf", # output pdf
                    # top hidden text with assignment
top=list(text=c('Adenoma Study','Patient: %__%','Treatment: %TREAT%'),
                col=c('orange','blue','red'),font=c(1,1,4)),
      # middle text to show through window of # 10 envelope 
    middle=list(text=c("Adenoma Study","Stratum: %__%","Patient: %ID%"),
               col=c('black','red','cadetblue'),font=c(1,2,3)),
    # bottom text- any instructions to study coordinator
   bottom="Call 123-4567 to report patient entry. \nInstruct participant to avoid antibiotics and stop aspirin",
   cut.marks=TRUE) # add cut marks - 4 per page