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Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random 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 not systematic at 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, and controlling are key aspects of the design of experiments because they help ensure that the results are not spurious or deceptive via confounding. This is why randomized controlled trials are vital in clinical research, especially ones that can be double-blinded and placebo-controlled.
Mathematically, there are distinctions between randomization, pseudorandomization, and quasirandomization, as well as between random number generators and pseudorandom number generators. How much these differences matter in experiments (such as clinical trials) is a matter of trial design and statistical rigor, which affect evidence 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 the mean it may be discovered that they differ, even though they were assigned from the same group. If a test of statistical significance is applied to randomly assigned groups to test the difference between sample means against the null hypothesis that 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 of Charles S. Peirce in "Illustrations of the Logic of Science" (1877–1878) and "A Theory of Probable Inference" (1883). Peirce applied randomization in the Peirce-Jastrow experiment on weight perception.
Charles S. Peirce randomly assigned volunteers to a blinded, repeated-measures design to evaluate their ability to discriminate weights. Peirce's experiment inspired other researchers in psychology and education, which developed a research tradition of randomized experiments in laboratories and specialized textbooks in the eighteen-hundreds.
Jerzy Neyman advocated randomization in survey sampling (1934) and in experiments (1923).Ronald A. Fisher advocated randomization in his book on experimental design (1935).
See also
- Asymptotic theory (statistics)
References
- Witte, Robert S. (5 January 2017). Statistics. Witte, John S. (11 ed.). Hoboken, NJ. p. 5. ISBN 978-1-119-25451-5. OCLC 956984834.
{{cite book}}: CS1 maint: location missing publisher (link) - Charles Sanders Peirce and Joseph Jastrow (1885). "On Small Differences in Sensation". Memoirs of the National Academy of Sciences. 3: 73–83.
- Ian Hacking (September 1988). "Telepathy: Origins of Randomization in Experimental Design". Isis. 79 (3): 427–451. doi:10.1086/354775. S2CID 52201011.
- 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. S2CID 143685203.
- 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. PMID 9519574. S2CID 23526321.
- Neyman, Jerzy (1990) [1923], Dabrowska, Dorota M.; Speed, Terence P. (eds.), "On the application of probability theory to agricultural experiments: Essay on principles (Section 9)", Statistical Science, 5 (4) (Translated from (1923) Polish ed.): 465–472, doi:10.1214/ss/1177012031, MR 1092986
- Caliński, Tadeusz & Kageyama, Sanpei (2000). Block designs: A Randomization approach, Volume I: Analysis. Lecture Notes in Statistics. Vol. 150. New York: Springer-Verlag. ISBN 0-387-98578-6.
- Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments. Vol. I and II (Second ed.). Wiley. ISBN 978-0-470-38551-7.
{{cite book}}: CS1 maint: multiple names: authors list (link)- Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (Second ed.). Wiley. ISBN 978-0-471-72756-9.
{{cite book}}: CS1 maint: multiple names: authors list (link) - Hinkelmann, Klaus and Kempthorne, Oscar (2005). Design and Analysis of Experiments, Volume 2: Advanced Assignment Experimental Design (First ed.). Wiley. ISBN 978-0-471-55177-5.
{{cite book}}: External link in|title=
- Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (Second ed.). Wiley. ISBN 978-0-471-72756-9.
- Charles S. Peirce, "Illustrations of the Logic of Science" (1877–1878)
- Charles S. Peirce, "A Theory of Probable Inference" (1883)
- Charles Sanders Peirce and Joseph 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. JSTOR 234674. MR 1013489. S2CID 52201011.
- 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. S2CID 143685203.
- 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. PMID 9519574. S2CID 23526321.
- Basic Psychology by 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
This article has multiple issues Please help improve it or discuss these issues on the talk page Learn how and when to remove these messages This article includes a list of general references but it lacks sufficient corresponding inline citations Please help to improve this article by introducing more precise citations May 2016 Learn how and when to remove this message This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Random assignment news newspapers books scholar JSTOR May 2016 Learn how and when to remove this message Learn how and when to remove this message Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment e g a treatment group versus a control group using randomization such as by a chance procedure e g flipping a coin or a random 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 not systematic at 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 and controlling are key aspects of the design of experiments because they help ensure that the results are not spurious or deceptive via confounding This is why randomized controlled trials are vital in clinical research especially ones that can be double blinded and placebo controlled Mathematically there are distinctions between randomization pseudorandomization and quasirandomization as well as between random number generators and pseudorandom number generators How much these differences matter in experiments such as clinical trials is a matter of trial design and statistical rigor which affect evidence 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 assignmentImagine 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 issuesRandom 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 the mean it may be discovered that they differ even though they were assigned from the same group If a test of statistical significance is applied to randomly assigned groups to test the difference between sample means against the null hypothesis that 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 samplingRandom 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 HistoryRandomization was emphasized in the theory of statistical inference of Charles S Peirce in Illustrations of the Logic of Science 1877 1878 and A Theory of Probable Inference 1883 Peirce applied randomization in the Peirce Jastrow experiment on weight perception Charles S Peirce randomly assigned volunteers to a blinded repeated measures design to evaluate their ability to discriminate weights Peirce s experiment inspired other researchers in psychology and education which developed a research tradition of randomized experiments in laboratories and specialized textbooks in the eighteen hundreds Jerzy Neyman advocated randomization in survey sampling 1934 and in experiments 1923 Ronald A Fisher advocated randomization in his book on experimental design 1935 See alsoAsymptotic theory statistics ReferencesWitte Robert S 5 January 2017 Statistics Witte John S 11 ed Hoboken NJ p 5 ISBN 978 1 119 25451 5 OCLC 956984834 a href wiki Template Cite book title Template Cite book cite book a CS1 maint location missing publisher link Social Research Methods Knowledge Base Random Selection amp Assignment Charles Sanders Peirce and Joseph Jastrow 1885 On Small Differences in Sensation Memoirs of the National Academy of Sciences 3 73 83 Ian Hacking September 1988 Telepathy Origins of Randomization in Experimental Design Isis 79 3 427 451 doi 10 1086 354775 S2CID 52201011 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 S2CID 143685203 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 PMID 9519574 S2CID 23526321 Neyman Jerzy 1990 1923 Dabrowska Dorota M Speed Terence P eds On the application of probability theory to agricultural experiments Essay on principles Section 9 Statistical Science 5 4 Translated from 1923 Polish ed 465 472 doi 10 1214 ss 1177012031 MR 1092986 Calinski Tadeusz amp Kageyama Sanpei 2000 Block designs A Randomization approach Volume I Analysis Lecture Notes in Statistics Vol 150 New York Springer Verlag ISBN 0 387 98578 6 Hinkelmann Klaus and Kempthorne Oscar 2008 Design and Analysis of Experiments Vol I and II Second ed Wiley ISBN 978 0 470 38551 7 a href wiki Template Cite book title Template Cite book cite book a CS1 maint multiple names authors list link Hinkelmann Klaus and Kempthorne Oscar 2008 Design and Analysis of Experiments Volume I Introduction to Experimental Design Second ed Wiley ISBN 978 0 471 72756 9 a href wiki Template Cite book title Template Cite book cite book a CS1 maint multiple names authors list link Hinkelmann Klaus and Kempthorne Oscar 2005 Design and Analysis of Experiments Volume 2 Advanced Assignment Experimental Design First ed Wiley ISBN 978 0 471 55177 5 a href wiki Template Cite book title Template Cite book cite book a External link in code class cs1 code title code 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 Peirce and Joseph 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 JSTOR 234674 MR 1013489 S2CID 52201011 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 S2CID 143685203 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 PMID 9519574 S2CID 23526321 Basic Psychology by 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 linksExperimental Random Assignment Tool Random assignment tool Experimental
