Original post by Olivia Williams:
What are some of the best methods to create randomization in study samples?
I am basing this response off of an article from the Journal of Clinics in Orthopedic Surgery (Kim and Shin 2014). I gathered two fancy terms for techniques to create accurate results in studies using randomization:
Allocation Concealment- a method used to get rid of selection bias by hiding the allocation sequence from those assigning participants to intervention groups as it inhibits researchers from influencing which participants are assigned to a given intervention group (Kim and Shin 2014)
Blinding- a method used to keep trial participants, health care providers, assessors or data collectors unaware of the assigned intervention which minimizes possible bias in implementation, dropouts, measurements, etc. (Kim and Shin 2014)
Further, there are common programs used for randomization i.e. excel. The authors explain due to the nature of Excel, if there is a change, it creates a new random number accordingly. The article provides a template you are able to download. It was created with the read-only setting to prevent accidental modification (Kim and Shin 2014). You can even change the size of the total sample and use the AutoFill function, as well.
Kim, Jeehyoung, Wonshik Shin. 2014. “How to Do Random Allocation (Randomization)”. Journal of Clinics in Orthopedic Surgery. Vol. 6(1): pp. 103–109.