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 3 CS/Tofa
## 2 BfLA02 Bfail.LowAlb BfLA01 3 CS/Upa
## 3 BfLA03 Bfail.LowAlb BfLA01 3 CS
## 4 BfLA04 Bfail.LowAlb BfLA02 3 CS/Tofa
## 5 BfLA05 Bfail.LowAlb BfLA02 3 CS/Upa
## 6 BfLA06 Bfail.LowAlb BfLA02 3 CS
## 7 BfLA07 Bfail.LowAlb BfLA03 3 CS/Tofa
## 8 BfLA08 Bfail.LowAlb BfLA03 3 CS/Upa
## 9 BfLA09 Bfail.LowAlb BfLA03 3 CS
## 10 BfLA10 Bfail.LowAlb BfLA04 3 CS
## 11 BfLA11 Bfail.LowAlb BfLA04 3 CS/Upa
## 12 BfLA12 Bfail.LowAlb BfLA04 3 CS/Tofa
## 13 BfLA13 Bfail.LowAlb BfLA05 3 CS/Upa
## 14 BfLA14 Bfail.LowAlb BfLA05 3 CS/Tofa
## 15 BfLA15 Bfail.LowAlb BfLA05 3 CS
## 16 BfLA16 Bfail.LowAlb BfLA06 3 CS/Upa
## 17 BfLA17 Bfail.LowAlb BfLA06 3 CS/Tofa
## 18 BfLA18 Bfail.LowAlb BfLA06 3 CS
## 19 BfLA19 Bfail.LowAlb BfLA07 3 CS/Upa
## 20 BfLA20 Bfail.LowAlb BfLA07 3 CS/Tofa
## 21 BfLA21 Bfail.LowAlb BfLA07 3 CS
## 22 BfLA22 Bfail.LowAlb BfLA08 3 CS
## 23 BfLA23 Bfail.LowAlb BfLA08 3 CS/Upa
## 24 BfLA24 Bfail.LowAlb BfLA08 3 CS/Tofa
## 25 BfLA25 Bfail.LowAlb BfLA09 3 CS
## 26 BfLA26 Bfail.LowAlb BfLA09 3 CS/Tofa
## 27 BfLA27 Bfail.LowAlb BfLA09 3 CS/Upa
## 28 BfLA28 Bfail.LowAlb BfLA10 9 CS/Tofa
## 29 BfLA29 Bfail.LowAlb BfLA10 9 CS
## 30 BfLA30 Bfail.LowAlb BfLA10 9 CS/Tofa
## 31 BfLA31 Bfail.LowAlb BfLA10 9 CS/Upa
## 32 BfLA32 Bfail.LowAlb BfLA10 9 CS/Tofa
## 33 BfLA33 Bfail.LowAlb BfLA10 9 CS/Upa
## 34 BfLA34 Bfail.LowAlb BfLA10 9 CS
## 35 BfLA35 Bfail.LowAlb BfLA10 9 CS
## 36 BfLA36 Bfail.LowAlb BfLA10 9 CS/Upa
## 37 BfLA37 Bfail.LowAlb BfLA11 6 CS/Tofa
## 38 BfLA38 Bfail.LowAlb BfLA11 6 CS/Tofa
## 39 BfLA39 Bfail.LowAlb BfLA11 6 CS/Upa
## 40 BfLA40 Bfail.LowAlb BfLA11 6 CS/Upa
## 41 BfLA41 Bfail.LowAlb BfLA11 6 CS
## 42 BfLA42 Bfail.LowAlb BfLA11 6 CS
## 43 BfLA43 Bfail.LowAlb BfLA12 3 CS
## 44 BfLA44 Bfail.LowAlb BfLA12 3 CS/Upa
## 45 BfLA45 Bfail.LowAlb BfLA12 3 CS/Tofa
## 46 BfLA46 Bfail.LowAlb BfLA13 9 CS/Tofa
## 47 BfLA47 Bfail.LowAlb BfLA13 9 CS/Upa
## 48 BfLA48 Bfail.LowAlb BfLA13 9 CS/Tofa
## 49 BfLA49 Bfail.LowAlb BfLA13 9 CS
## 50 BfLA50 Bfail.LowAlb BfLA13 9 CS
## 51 BfLA51 Bfail.LowAlb BfLA13 9 CS
## 52 BfLA52 Bfail.LowAlb BfLA13 9 CS/Upa
## 53 BfLA53 Bfail.LowAlb BfLA13 9 CS/Tofa
## 54 BfLA54 Bfail.LowAlb BfLA13 9 CS/Upa
## 55 BfLA55 Bfail.LowAlb BfLA14 6 CS
## 56 BfLA56 Bfail.LowAlb BfLA14 6 CS/Upa
## 57 BfLA57 Bfail.LowAlb BfLA14 6 CS
## 58 BfLA58 Bfail.LowAlb BfLA14 6 CS/Tofa
## 59 BfLA59 Bfail.LowAlb BfLA14 6 CS/Upa
## 60 BfLA60 Bfail.LowAlb BfLA14 6 CS/TofaYou 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 BfHA01 3 CS
## 2 BfHA02 Bfail.HiAlb BfHA01 3 CS/Tofa
## 3 BfHA03 Bfail.HiAlb BfHA01 3 CS/Upa
## 4 BfHA04 Bfail.HiAlb BfHA02 9 CS
## 5 BfHA05 Bfail.HiAlb BfHA02 9 CS
## 6 BfHA06 Bfail.HiAlb BfHA02 9 CS/Tofa
## 7 BfHA07 Bfail.HiAlb BfHA02 9 CS/Tofa
## 8 BfHA08 Bfail.HiAlb BfHA02 9 CS/Upa
## 9 BfHA09 Bfail.HiAlb BfHA02 9 CS/Tofa
## 10 BfHA10 Bfail.HiAlb BfHA02 9 CS
## 11 BfHA11 Bfail.HiAlb BfHA02 9 CS/Upa
## 12 BfHA12 Bfail.HiAlb BfHA02 9 CS/Upa
## 13 BfHA13 Bfail.HiAlb BfHA03 3 CS/Tofa
## 14 BfHA14 Bfail.HiAlb BfHA03 3 CS
## 15 BfHA15 Bfail.HiAlb BfHA03 3 CS/Upa
## 16 BfHA16 Bfail.HiAlb BfHA04 6 CS
## 17 BfHA17 Bfail.HiAlb BfHA04 6 CS/Upa
## 18 BfHA18 Bfail.HiAlb BfHA04 6 CS
## 19 BfHA19 Bfail.HiAlb BfHA04 6 CS/Upa
## 20 BfHA20 Bfail.HiAlb BfHA04 6 CS/Tofa
## 21 BfHA21 Bfail.HiAlb BfHA04 6 CS/Tofa
## 22 BfHA22 Bfail.HiAlb BfHA05 3 CS
## 23 BfHA23 Bfail.HiAlb BfHA05 3 CS/Upa
## 24 BfHA24 Bfail.HiAlb BfHA05 3 CS/Tofa
## 25 BfHA25 Bfail.HiAlb BfHA06 6 CS/Upa
## 26 BfHA26 Bfail.HiAlb BfHA06 6 CS
## 27 BfHA27 Bfail.HiAlb BfHA06 6 CS/Tofa
## 28 BfHA28 Bfail.HiAlb BfHA06 6 CS
## 29 BfHA29 Bfail.HiAlb BfHA06 6 CS/Upa
## 30 BfHA30 Bfail.HiAlb BfHA06 6 CS/Tofa
## 31 BfHA31 Bfail.HiAlb BfHA07 3 CS
## 32 BfHA32 Bfail.HiAlb BfHA07 3 CS/Tofa
## 33 BfHA33 Bfail.HiAlb BfHA07 3 CS/Upa
## 34 BfHA34 Bfail.HiAlb BfHA08 3 CS/Upa
## 35 BfHA35 Bfail.HiAlb BfHA08 3 CS/Tofa
## 36 BfHA36 Bfail.HiAlb BfHA08 3 CS
## 37 BfHA37 Bfail.HiAlb BfHA09 6 CS
## 38 BfHA38 Bfail.HiAlb BfHA09 6 CS/Upa
## 39 BfHA39 Bfail.HiAlb BfHA09 6 CS/Upa
## 40 BfHA40 Bfail.HiAlb BfHA09 6 CS/Tofa
## 41 BfHA41 Bfail.HiAlb BfHA09 6 CS
## 42 BfHA42 Bfail.HiAlb BfHA09 6 CS/Tofa
## 43 BfHA43 Bfail.HiAlb BfHA10 9 CS/Upa
## 44 BfHA44 Bfail.HiAlb BfHA10 9 CS/Tofa
## 45 BfHA45 Bfail.HiAlb BfHA10 9 CS/Upa
## 46 BfHA46 Bfail.HiAlb BfHA10 9 CS
## 47 BfHA47 Bfail.HiAlb BfHA10 9 CS/Tofa
## 48 BfHA48 Bfail.HiAlb BfHA10 9 CS/Upa
## 49 BfHA49 Bfail.HiAlb BfHA10 9 CS
## 50 BfHA50 Bfail.HiAlb BfHA10 9 CS/Tofa
## 51 BfHA51 Bfail.HiAlb BfHA10 9 CS
## 52 BfHA52 Bfail.HiAlb BfHA11 9 CS/Tofa
## 53 BfHA53 Bfail.HiAlb BfHA11 9 CS/Tofa
## 54 BfHA54 Bfail.HiAlb BfHA11 9 CS/Upa
## 55 BfHA55 Bfail.HiAlb BfHA11 9 CS
## 56 BfHA56 Bfail.HiAlb BfHA11 9 CS/Upa
## 57 BfHA57 Bfail.HiAlb BfHA11 9 CS/Tofa
## 58 BfHA58 Bfail.HiAlb BfHA11 9 CS
## 59 BfHA59 Bfail.HiAlb BfHA11 9 CS/Upa
## 60 BfHA60 Bfail.HiAlb BfHA11 9 CSbnha <- 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 BnHA01 3 CS
## 2 BnHA02 Bnaive.HiAlb BnHA01 3 CS/Upa
## 3 BnHA03 Bnaive.HiAlb BnHA01 3 CS/Tofa
## 4 BnHA04 Bnaive.HiAlb BnHA02 6 CS/Tofa
## 5 BnHA05 Bnaive.HiAlb BnHA02 6 CS/Upa
## 6 BnHA06 Bnaive.HiAlb BnHA02 6 CS/Tofa
## 7 BnHA07 Bnaive.HiAlb BnHA02 6 CS/Upa
## 8 BnHA08 Bnaive.HiAlb BnHA02 6 CS
## 9 BnHA09 Bnaive.HiAlb BnHA02 6 CS
## 10 BnHA10 Bnaive.HiAlb BnHA03 6 CS/Tofa
## 11 BnHA11 Bnaive.HiAlb BnHA03 6 CS
## 12 BnHA12 Bnaive.HiAlb BnHA03 6 CS/Tofa
## 13 BnHA13 Bnaive.HiAlb BnHA03 6 CS/Upa
## 14 BnHA14 Bnaive.HiAlb BnHA03 6 CS/Upa
## 15 BnHA15 Bnaive.HiAlb BnHA03 6 CS
## 16 BnHA16 Bnaive.HiAlb BnHA04 3 CS
## 17 BnHA17 Bnaive.HiAlb BnHA04 3 CS/Upa
## 18 BnHA18 Bnaive.HiAlb BnHA04 3 CS/Tofa
## 19 BnHA19 Bnaive.HiAlb BnHA05 6 CS/Tofa
## 20 BnHA20 Bnaive.HiAlb BnHA05 6 CS
## 21 BnHA21 Bnaive.HiAlb BnHA05 6 CS
## 22 BnHA22 Bnaive.HiAlb BnHA05 6 CS/Tofa
## 23 BnHA23 Bnaive.HiAlb BnHA05 6 CS/Upa
## 24 BnHA24 Bnaive.HiAlb BnHA05 6 CS/Upa
## 25 BnHA25 Bnaive.HiAlb BnHA06 3 CS/Tofa
## 26 BnHA26 Bnaive.HiAlb BnHA06 3 CS/Upa
## 27 BnHA27 Bnaive.HiAlb BnHA06 3 CS
## 28 BnHA28 Bnaive.HiAlb BnHA07 6 CS/Tofa
## 29 BnHA29 Bnaive.HiAlb BnHA07 6 CS/Upa
## 30 BnHA30 Bnaive.HiAlb BnHA07 6 CS
## 31 BnHA31 Bnaive.HiAlb BnHA07 6 CS
## 32 BnHA32 Bnaive.HiAlb BnHA07 6 CS/Upa
## 33 BnHA33 Bnaive.HiAlb BnHA07 6 CS/Tofa
## 34 BnHA34 Bnaive.HiAlb BnHA08 6 CS
## 35 BnHA35 Bnaive.HiAlb BnHA08 6 CS/Tofa
## 36 BnHA36 Bnaive.HiAlb BnHA08 6 CS/Upa
## 37 BnHA37 Bnaive.HiAlb BnHA08 6 CS
## 38 BnHA38 Bnaive.HiAlb BnHA08 6 CS/Tofa
## 39 BnHA39 Bnaive.HiAlb BnHA08 6 CS/Upa
## 40 BnHA40 Bnaive.HiAlb BnHA09 6 CS
## 41 BnHA41 Bnaive.HiAlb BnHA09 6 CS/Tofa
## 42 BnHA42 Bnaive.HiAlb BnHA09 6 CS/Upa
## 43 BnHA43 Bnaive.HiAlb BnHA09 6 CS
## 44 BnHA44 Bnaive.HiAlb BnHA09 6 CS/Tofa
## 45 BnHA45 Bnaive.HiAlb BnHA09 6 CS/Upa
## 46 BnHA46 Bnaive.HiAlb BnHA10 3 CS/Tofa
## 47 BnHA47 Bnaive.HiAlb BnHA10 3 CS/Upa
## 48 BnHA48 Bnaive.HiAlb BnHA10 3 CS
## 49 BnHA49 Bnaive.HiAlb BnHA11 6 CS/Upa
## 50 BnHA50 Bnaive.HiAlb BnHA11 6 CS/Tofa
## 51 BnHA51 Bnaive.HiAlb BnHA11 6 CS/Upa
## 52 BnHA52 Bnaive.HiAlb BnHA11 6 CS
## 53 BnHA53 Bnaive.HiAlb BnHA11 6 CS/Tofa
## 54 BnHA54 Bnaive.HiAlb BnHA11 6 CS
## 55 BnHA55 Bnaive.HiAlb BnHA12 9 CS
## 56 BnHA56 Bnaive.HiAlb BnHA12 9 CS
## 57 BnHA57 Bnaive.HiAlb BnHA12 9 CS/Upa
## 58 BnHA58 Bnaive.HiAlb BnHA12 9 CS/Tofa
## 59 BnHA59 Bnaive.HiAlb BnHA12 9 CS/Tofa
## 60 BnHA60 Bnaive.HiAlb BnHA12 9 CS/Upa
## 61 BnHA61 Bnaive.HiAlb BnHA12 9 CS/Upa
## 62 BnHA62 Bnaive.HiAlb BnHA12 9 CS/Tofa
## 63 BnHA63 Bnaive.HiAlb BnHA12 9 CSbnla <- 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/Upa
## 2 BnLA02 Bnaive.LoAlb BnLA01 6 CS
## 3 BnLA03 Bnaive.LoAlb BnLA01 6 CS/Upa
## 4 BnLA04 Bnaive.LoAlb BnLA01 6 CS
## 5 BnLA05 Bnaive.LoAlb BnLA01 6 CS/Tofa
## 6 BnLA06 Bnaive.LoAlb BnLA01 6 CS/Tofa
## 7 BnLA07 Bnaive.LoAlb BnLA02 6 CS/Tofa
## 8 BnLA08 Bnaive.LoAlb BnLA02 6 CS/Upa
## 9 BnLA09 Bnaive.LoAlb BnLA02 6 CS/Tofa
## 10 BnLA10 Bnaive.LoAlb BnLA02 6 CS
## 11 BnLA11 Bnaive.LoAlb BnLA02 6 CS
## 12 BnLA12 Bnaive.LoAlb BnLA02 6 CS/Upa
## 13 BnLA13 Bnaive.LoAlb BnLA03 9 CS
## 14 BnLA14 Bnaive.LoAlb BnLA03 9 CS/Upa
## 15 BnLA15 Bnaive.LoAlb BnLA03 9 CS
## 16 BnLA16 Bnaive.LoAlb BnLA03 9 CS/Tofa
## 17 BnLA17 Bnaive.LoAlb BnLA03 9 CS/Tofa
## 18 BnLA18 Bnaive.LoAlb BnLA03 9 CS/Tofa
## 19 BnLA19 Bnaive.LoAlb BnLA03 9 CS/Upa
## 20 BnLA20 Bnaive.LoAlb BnLA03 9 CS
## 21 BnLA21 Bnaive.LoAlb BnLA03 9 CS/Upa
## 22 BnLA22 Bnaive.LoAlb BnLA04 9 CS/Upa
## 23 BnLA23 Bnaive.LoAlb BnLA04 9 CS/Upa
## 24 BnLA24 Bnaive.LoAlb BnLA04 9 CS
## 25 BnLA25 Bnaive.LoAlb BnLA04 9 CS/Tofa
## 26 BnLA26 Bnaive.LoAlb BnLA04 9 CS
## 27 BnLA27 Bnaive.LoAlb BnLA04 9 CS/Tofa
## 28 BnLA28 Bnaive.LoAlb BnLA04 9 CS/Upa
## 29 BnLA29 Bnaive.LoAlb BnLA04 9 CS/Tofa
## 30 BnLA30 Bnaive.LoAlb BnLA04 9 CS
## 31 BnLA31 Bnaive.LoAlb BnLA05 3 CS/Upa
## 32 BnLA32 Bnaive.LoAlb BnLA05 3 CS/Tofa
## 33 BnLA33 Bnaive.LoAlb BnLA05 3 CS
## 34 BnLA34 Bnaive.LoAlb BnLA06 6 CS/Upa
## 35 BnLA35 Bnaive.LoAlb BnLA06 6 CS/Upa
## 36 BnLA36 Bnaive.LoAlb BnLA06 6 CS
## 37 BnLA37 Bnaive.LoAlb BnLA06 6 CS/Tofa
## 38 BnLA38 Bnaive.LoAlb BnLA06 6 CS
## 39 BnLA39 Bnaive.LoAlb BnLA06 6 CS/Tofa
## 40 BnLA40 Bnaive.LoAlb BnLA07 6 CS
## 41 BnLA41 Bnaive.LoAlb BnLA07 6 CS/Tofa
## 42 BnLA42 Bnaive.LoAlb BnLA07 6 CS
## 43 BnLA43 Bnaive.LoAlb BnLA07 6 CS/Upa
## 44 BnLA44 Bnaive.LoAlb BnLA07 6 CS/Upa
## 45 BnLA45 Bnaive.LoAlb BnLA07 6 CS/Tofa
## 46 BnLA46 Bnaive.LoAlb BnLA08 6 CS/Upa
## 47 BnLA47 Bnaive.LoAlb BnLA08 6 CS/Upa
## 48 BnLA48 Bnaive.LoAlb BnLA08 6 CS
## 49 BnLA49 Bnaive.LoAlb BnLA08 6 CS/Tofa
## 50 BnLA50 Bnaive.LoAlb BnLA08 6 CS/Tofa
## 51 BnLA51 Bnaive.LoAlb BnLA08 6 CS
## 52 BnLA52 Bnaive.LoAlb BnLA09 3 CS/Upa
## 53 BnLA53 Bnaive.LoAlb BnLA09 3 CS
## 54 BnLA54 Bnaive.LoAlb BnLA09 3 CS/Tofa
## 55 BnLA55 Bnaive.LoAlb BnLA10 6 CS/Upa
## 56 BnLA56 Bnaive.LoAlb BnLA10 6 CS/Upa
## 57 BnLA57 Bnaive.LoAlb BnLA10 6 CS
## 58 BnLA58 Bnaive.LoAlb BnLA10 6 CS
## 59 BnLA59 Bnaive.LoAlb BnLA10 6 CS/Tofa
## 60 BnLA60 Bnaive.LoAlb BnLA10 6 CS/Tofa20.1 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 pageOpen 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_pamNow 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_pamGreat!
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 page20.3 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
mhbhEdit 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
mlbhEdit 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