Random assignment

Random assignmentorrandom placementis anexperimentaltechnique for assigninghuman participantsoranimal subjectsto different groups in an experiment (e.g.,a treatment group versus a control group) usingrandomization,such as by a chance procedure (e.g.,flipping a coin) or arandom number generator.This ensures that each participant or subject has an equal chance of being placed in any group.Random assignment of participants helps to ensure that any differences between and within the groups are notsystematicat the outset of the experiment.Thus, any differences between groups recorded at the end of the experiment can be more confidently attributed to the experimental procedures or treatment.

Random assignment,blinding,andcontrollingare key aspects of thedesign of experimentsbecause they help ensure that the results are not spurious or deceptive viaconfounding.This is whyrandomized controlled trialsare vital inclinical research,especially ones that can bedouble-blindedandplacebo-controlled.

Mathematically, there are distinctions between randomization,pseudorandomization,andquasirandomization,as well as betweenrandom number generatorsandpseudorandom number generators.How much these differences matter in experiments (such asclinical trials) is a matter oftrial designandstatisticalrigor, which affectevidence grading.Studies done with pseudo- or quasirandomization are usually given nearly the same weight as those with true randomization but are viewed with a bit more caution.

Benefits of random assignment

Imagine an experiment in which the participants are not randomly assigned; perhaps the first 10 people to arrive are assigned to the Experimental group, and the last 10 people to arrive are assigned to the Control group. At the end of the experiment, the experimenter finds differences between the Experimental group and the Control group, and claims these differences are a result of the experimental procedure. However, they also may be due to some other preexisting attribute of the participants, e.g. people who arrive early versus people who arrive late.

Imagine the experimenter instead uses a coin flip to randomly assign participants. If the coin lands heads-up, the participant is assigned to the Experimental group. If the coin lands tails-up, the participant is assigned to the Control group. At the end of the experiment, the experimenter finds differences between the Experimental group and the Control group. Because each participant had an equal chance of being placed in any group, it is unlikely the differences could be attributable to some other preexisting attribute of the participant, e.g. those who arrived on time versus late.

Potential issues

Random assignment does not guarantee that the groups are matched or equivalent. The groups may still differ on some preexisting attribute due to chance. The use of random assignment cannot eliminate this possibility, but it greatly reduces it.

To express this same idea statistically - If a randomly assigned group is compared to themeanit may be discovered that they differ, even though they were assigned from the same group. If a test ofstatistical significanceis applied to randomly assigned groups to test the difference between samplemeansagainst thenull hypothesisthat they are equal to the same population mean (i.e., population mean of differences = 0), given the probability distribution, the null hypothesis will sometimes be "rejected," that is, deemed not plausible. That is, the groups will be sufficiently different on the variable tested to conclude statistically that they did not come from the same population, even though, procedurally, they were assigned from the same total group. For example, using random assignment may create an assignment to groups that has 20 blue-eyed people and 5 brown-eyed people in one group. This is a rare event under random assignment, but it could happen, and when it does it might add some doubt to the causal agent in the experimental hypothesis.

Random sampling

Random sampling is a related, but distinct, process.Random sampling is recruiting participants in a way that they represent a larger population.Because most basic statistical tests require the hypothesis of an independent randomly sampled population, random assignment is the desired assignment method because it provides control for all attributes of the members of the samples—in contrast to matching on only one or more variables—and provides the mathematical basis for estimating the likelihood of group equivalence for characteristics one is interested in, both for pretreatment checks on equivalence and the evaluation of post treatment results using inferential statistics. More advanced statistical modeling can be used to adapt the inference to the sampling method.

History

Randomization was emphasized in the theory of statistical inference ofCharles S. Peircein "Illustrations of the Logic of Science"(1877–1878) and"A Theory of Probable Inference"(1883). Peirce applied randomization in the Peirce-Jastrowexperiment on weight perception.

Charles S. Peirce randomly assigned volunteers to ablinded,repeated-measures designto evaluate their ability to discriminate weights. Peirce's experiment inspired other researchers in psychology and education, which developed a research tradition ofrandomized experimentsin laboratories and specialized textbooks in the eighteen-hundreds.

Jerzy Neymanadvocated randomization in survey sampling (1934) and in experiments (1923).Ronald A. Fisheradvocated randomization in hisbookonexperimental design(1935).

See also

• Asymptotic theory (statistics)

References

• Caliński, Tadeusz & Kageyama, Sanpei (2000).Block designs: A Randomization approach, VolumeI:Analysis.Lecture Notes in Statistics. Vol. 150. New York: Springer-Verlag.ISBN0-387-98578-6.
• Hinkelmann, Klaus andKempthorne, Oscar(2008).Design and Analysis of Experiments.Vol. I and II (Second ed.). Wiley.ISBN978-0-470-38551-7.{{cite book}}:CS1 maint: multiple names: authors list (link)
  • Hinkelmann, Klaus andKempthorne, Oscar(2008).Design and Analysis of Experiments, Volume I: Introduction to Experimental Design(Second ed.). Wiley.ISBN978-0-471-72756-9.{{cite book}}:CS1 maint: multiple names: authors list (link)
  • Hinkelmann, Klaus andKempthorne, Oscar(2005).Design and Analysis of Experiments, Volume 2: AdvancedAssignmentExperimental Design(First ed.). Wiley.ISBN978-0-471-55177-5.{{cite book}}:External link in|title=(help)CS1 maint: multiple names: authors list (link)
• Charles S. Peirce,"Illustrations of the Logic of Science"(1877–1878)
• Charles S. Peirce,"A Theory of Probable Inference"(1883)
• Charles Sanders PeirceandJoseph Jastrow(1885)."On Small Differences in Sensation".Memoirs of the National Academy of Sciences.3:73–83.http://psychclassics.yorku.ca/Peirce/small-diffs.htm
• Hacking, Ian(September 1988). "Telepathy: Origins of Randomization in Experimental Design".Isis.79(3): 427–451.doi:10.1086/354775.JSTOR234674.MR1013489.S2CID52201011.
• Stephen M. Stigler(November 1992). "A Historical View of Statistical Concepts in Psychology and Educational Research".American Journal of Education.101(1): 60–70.doi:10.1086/444032.S2CID143685203.
• Trudy Dehue (December 1997)."Deception, Efficiency, and Random Groups: Psychology and the Gradual Origination of the Random Group Design"(PDF).Isis.88(4): 653–673.doi:10.1086/383850.PMID9519574.S2CID23526321.
• Basic Psychologyby Gleitman, Fridlund, and Reisberg.
• "What statistical testing is, and what it is not,"Journal of Experimental Education,1993, vol 61, pp. 293–316 by Shaver.

External links

• Experimental Random Assignment Tool:Random assignment tool - Experimental