%0 Journal Article %1 Matthews2010 %A Matthews, Ellyn E %A Cook, Paul F %A Terada, Masaka %A Aloia, Mark S %D 2010 %J Research in nursing & health %K Bias(Epidemiology) Biometry Biometry:methods Humans Models RandomizedControlledTrialsasTopic:statistics SampleSize Statistical RCT %N 3 %P 243-53 %R 10.1002/nur.20375 %T Randomizing research participants: promoting balance and concealment in small samples. %U http://www.ncbi.nlm.nih.gov/pubmed/20499394 %V 33 %X Randomization is central to rigorous scientific trials. An effective but underutilized approach is urn randomization. To test the ability of urn randomization versus simple randomization to produce balanced groups with small sample sizes, we conducted simulated randomizations: 10 times under sample size scenarios of 20, 40, 60 (group sizes of 10, 20, and 30, respectively), for 30 trials in total. For groups of 20-30, urn surpassed simple randomization in the equal distribution of confounding variables between groups, leading to effects of these variables that were both smaller on average and more consistently close to zero over multiple trials. The urn method is easy to implement and has the advantages of unpredictability of assignment and decreased susceptibility to investigator bias. %@ 1098-240X; 0160-6891

@article{Matthews2010, abstract = {Randomization is central to rigorous scientific trials. An effective but underutilized approach is urn randomization. To test the ability of urn randomization versus simple randomization to produce balanced groups with small sample sizes, we conducted simulated randomizations: 10 times under sample size scenarios of 20, 40, 60 (group sizes of 10, 20, and 30, respectively), for 30 trials in total. For groups of 20-30, urn surpassed simple randomization in the equal distribution of confounding variables between groups, leading to effects of these variables that were both smaller on average and more consistently close to zero over multiple trials. The urn method is easy to implement and has the advantages of unpredictability of assignment and decreased susceptibility to investigator bias.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Matthews, Ellyn E and Cook, Paul F and Terada, Masaka and Aloia, Mark S}, biburl = {https://www.bibsonomy.org/bibtex/272a7a916c05209ff7e3721dd7a275d54/jepcastel}, city = {College of Nursing, University of Colorado-Denver, 13120 E. 19th Ave., Aurora, CO 80045, USA.}, doi = {10.1002/nur.20375}, interhash = {5ec10b99a06a70c91ff89559866433c1}, intrahash = {72a7a916c05209ff7e3721dd7a275d54}, isbn = {1098-240X; 0160-6891}, issn = {1098-240X}, journal = {Research in nursing & health}, keywords = {Bias(Epidemiology) Biometry Biometry:methods Humans Models RandomizedControlledTrialsasTopic:statistics SampleSize Statistical RCT}, month = {6}, note = {5642<m:linebreak></m:linebreak>CI: (c) 2010; GR: 1UL1RR025780-01/RR/NCRR NIH HHS/United States; GR: NR010587/NR/NINR NIH HHS/United States; GR: NR04817/NR/NINR NIH HHS/United States; JID: 7806136; ppublish;<m:linebreak></m:linebreak>Aleatorització}, number = 3, pages = {243-53}, pmid = {20499394}, timestamp = {2023-05-04T09:00:45.000+0200}, title = {Randomizing research participants: promoting balance and concealment in small samples.}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20499394}, volume = 33, year = 2010 }