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Journal articles on the topic 'Randomization'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Hong, Jin Ho, and Jae Chul Yoo. "Randomization, What is the Proper Method?" Journal of the Korean Shoulder and Elbow Society 16, no. 1 (June 30, 2013): 58–62. http://dx.doi.org/10.5397/cise.2013.16.1.58.

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2

Barnbaum, Deborah R. "Randomization Among: The Other Randomization." Ethics & Human Research 41, no. 5 (September 2019): 35–40. http://dx.doi.org/10.1002/eahr.500031.

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3

Peto, Richard, and Rory Collins. "Randomization." Nature 372, no. 6507 (December 1994): 588. http://dx.doi.org/10.1038/372588d0.

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4

Manly, Bryan F. J. "Randomization." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 3 (April 22, 2010): 383–86. http://dx.doi.org/10.1002/wics.91.

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5

Zhang, Yanqiong, William F. Rosenberger, and Robert T. Smythe. "Sequential Monitoring of Randomization Tests: Stratified Randomization." Biometrics 63, no. 3 (January 23, 2007): 865–72. http://dx.doi.org/10.1111/j.1541-0420.2006.00735.x.

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6

Berger, Vance W., Klejda Bejleri, and Rebecca Agnor. "Comparing MTI randomization procedures to blocked randomization." Statistics in Medicine 35, no. 5 (September 3, 2015): 685–94. http://dx.doi.org/10.1002/sim.6637.

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7

ANDREWS, URI, and H. JEROME KEISLER. "SEPARABLE MODELS OF RANDOMIZATIONS." Journal of Symbolic Logic 80, no. 4 (December 2015): 1149–81. http://dx.doi.org/10.1017/jsl.2015.33.

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AbstractEvery complete first order theory has a corresponding complete theory in continuous logic, called the randomization theory. It has two sorts, a sort for random elements of models of the first order theory, and a sort for events. In this paper we establish connections between properties of countable models of a first order theory and corresponding properties of separable models of the randomization theory. We show that the randomization theory has a prime model if and only if the first order theory has a prime model. And the randomization theory has the same number of separable homogeneous models as the first order theory has countable homogeneous models. We also show that when T has at most countably many countable models, each separable model of TR is uniquely characterized by a probability density function on the set of isomorphism types of countable models of T. This yields an analogue for randomizations of the results of Baldwin and Lachlan on countable models of ω1-categorical first order theories.

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8

Bailey, R. A., and C. J. Brien. "Randomization-based models for multitiered experiments: I. A chain of randomizations." Annals of Statistics 44, no. 3 (June 2016): 1131–64. http://dx.doi.org/10.1214/15-aos1400.

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9

Mitchell-Olds, Thomas. "Randomization Methods." Ecology 73, no. 6 (December 1992): 2338–39. http://dx.doi.org/10.2307/1941484.

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10

Habibzadeh, Farrokh, and Parham Habibzadeh. "Shuffle randomization." Croatian Medical Journal 56, no. 4 (August 2015): 383–84. http://dx.doi.org/10.3325/cmj.2015.56.383.

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11

Ziegel, Eric R., and E. Edgington. "Randomization Tests." Technometrics 40, no. 2 (May 1998): 163. http://dx.doi.org/10.2307/1270665.

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12

Karlsson, Andreas. "Randomization Tests." Journal of the Royal Statistical Society: Series A (Statistics in Society) 171, no. 3 (June 2008): 757–58. http://dx.doi.org/10.1111/j.1467-985x.2008.00538_4.x.

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13

Kepler, Christopher K. "Randomization Strategies." Clinical Spine Surgery 30, no. 3 (April 2017): 120–21. http://dx.doi.org/10.1097/bsd.0000000000000523.

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14

Neeland, Ian J., and Julia Kozlitina. "Mendelian Randomization." Circulation 135, no. 8 (February 21, 2017): 755–58. http://dx.doi.org/10.1161/circulationaha.117.026857.

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15

Picard, John, and Jason Wilson. "Missing Randomization …" Anesthesiology 125, no. 2 (August 1, 2016): 417–18. http://dx.doi.org/10.1097/aln.0000000000001174.

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16

Hertsgaard, Doris. "Randomization Tests." Technometrics 31, no. 1 (February 1989): 127. http://dx.doi.org/10.1080/00401706.1989.10488498.

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17

Snowdon, Claire, Diana Elbourne, and Jo Garcia. "Zelen Randomization." Controlled Clinical Trials 20, no. 2 (April 1999): 149–71. http://dx.doi.org/10.1016/s0197-2456(98)00049-x.

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18

Nelson, Lloyd S. "Randomization Tests." Journal of Quality Technology 28, no. 1 (January 1996): 130–31. http://dx.doi.org/10.1080/00224065.1996.11979648.

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19

Aickin, Mikel. "Beyond Randomization." Journal of Alternative and Complementary Medicine 8, no. 6 (December 2002): 765–72. http://dx.doi.org/10.1089/10755530260511775.

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20

Schlittgen, R., and E. S. Edgington. "Randomization Tests." Journal of the Royal Statistical Society. Series A (Statistics in Society) 152, no. 1 (1989): 118. http://dx.doi.org/10.2307/2982830.

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21

Carrasco, Juan A., and Angel Calderón. "Regenerative randomization." ACM SIGMETRICS Performance Evaluation Review 23, no. 1 (May 1995): 241–52. http://dx.doi.org/10.1145/223586.223613.

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22

Thanassoulis, George, and Christopher J. O’Donnell. "Mendelian Randomization." JAMA 301, no. 22 (June 10, 2009): 2386. http://dx.doi.org/10.1001/jama.2009.812.

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23

Emdin, Connor A., Amit V. Khera, and Sekar Kathiresan. "Mendelian Randomization." JAMA 318, no. 19 (November 21, 2017): 1925. http://dx.doi.org/10.1001/jama.2017.17219.

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24

Pandis, Nikolaos. "Randomization. Part 3: Allocation concealment and randomization implementation." American Journal of Orthodontics and Dentofacial Orthopedics 141, no. 1 (January 2012): 126–28. http://dx.doi.org/10.1016/j.ajodo.2011.09.003.

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25

Korn, Edward L., and Boris Freidlin. "Outcome-Adaptive Randomization: Is It Useful?" Journal of Clinical Oncology 29, no. 6 (February 20, 2011): 771–76. http://dx.doi.org/10.1200/jco.2010.31.1423.

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Outcome-adaptive randomization is one of the possible elements of an adaptive trial design in which the ratio of patients randomly assigned to the experimental treatment arm versus the control treatment arm changes from 1:1 over time to randomly assigning a higher proportion of patients to the arm that is doing better. Outcome-adaptive randomization has intuitive appeal in that, on average, a higher proportion of patients will be treated on the better treatment arm (if there is one). In both the randomized phase II and phase III settings with a short-term binary outcome, we compare outcome-adaptive randomization with designs that use 1:1 and 2:1 fixed-ratio randomizations (in the latter, twice as many patients are randomly assigned to the experimental treatment arm). The comparisons are done in terms of required sample sizes, the numbers and proportions of patients having an inferior outcome, and we restrict attention to the situation in which one treatment arm is a control treatment (rather than the less common situation of two experimental treatments without a control treatment). With no differential patient accrual rates because of the trial design, we find no benefits to outcome-adaptive randomization over 1:1 randomization, and we recommend the latter. If it is thought that the patient accrual rates will be substantially higher because of the possibility of a higher proportion of patients being randomly assigned to the experimental treatment (because the trial will be more attractive to patients and clinicians), we recommend using a fixed 2:1 randomization instead of an outcome-adaptive randomization.

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26

Moerbeek, Mirjam. "Randomization of Clusters Versus Randomization of Persons Within Clusters." American Statistician 59, no. 1 (February 2005): 72–78. http://dx.doi.org/10.1198/000313005x20727.

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27

Moerbeek, Mirjam. "Randomization of Clusters Versus Randomization of Persons Within Clusters." American Statistician 59, no. 2 (May 2005): 173–79. http://dx.doi.org/10.1198/000313005x43542.

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28

Wang, Yanying, William F. Rosenberger, and Diane Uschner. "Randomization-based inference and the choice of randomization procedures." Statistical Papers 60, no. 2 (January 1, 2019): 395–404. http://dx.doi.org/10.1007/s00362-018-01070-y.

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29

Kuznetsova, Olga M., and Yevgen Tymofyeyev. "Shift in re-randomization distribution with conditional randomization test." Pharmaceutical Statistics 12, no. 2 (February 14, 2013): 82–91. http://dx.doi.org/10.1002/pst.1556.

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30

Cox, David R. "Randomization for concealment." Journal of the Royal Society of Medicine 103, no. 2 (January 29, 2010): 72–73. http://dx.doi.org/10.1258/jrsm.2009.09k064.

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31

Donner, A., and N. Klar. "Cluster randomization trials." Statistical Methods in Medical Research 9, no. 2 (April 1, 2000): 79–80. http://dx.doi.org/10.1191/096228000669355658.

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32

Ahlswede, R., and Ning Cai. "Identification without randomization." IEEE Transactions on Information Theory 45, no. 7 (1999): 2636–42. http://dx.doi.org/10.1109/18.796419.

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33

Berry, Scott M., and Joseph B. Kadane. "Optimal Bayesian Randomization." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 59, no. 4 (1997): 813–19. http://dx.doi.org/10.1111/1467-9868.00098.

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34

HAUCK, WALTER W., CATHERINE L. GILLISS, ALLAN DONNER, and SUSAN GORTNER. "Randomization by Cluster." Nursing Research 40, no. 6 (November 1991): 356???358. http://dx.doi.org/10.1097/00006199-199111000-00007.

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35

Fox, Mark D., Chan M. Hellman, and Martina R. Jelley. "Equipoise Trumps Randomization." American Journal of Bioethics 9, no. 2 (February 16, 2009): 13–14. http://dx.doi.org/10.1080/15265160802669408.

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36

Ference, Brian A. "Mendelian randomization studies." Current Opinion in Lipidology 26, no. 6 (December 2015): 566–71. http://dx.doi.org/10.1097/mol.0000000000000247.

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37

Rhodes, William. "Pairwise Cluster Randomization." Evaluation Review 38, no. 3 (June 2014): 217–50. http://dx.doi.org/10.1177/0193841x14540654.

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38

Chaytor, Rhonda, and Ke Wang. "Small domain randomization." Proceedings of the VLDB Endowment 3, no. 1-2 (September 2010): 608–18. http://dx.doi.org/10.14778/1920841.1920919.

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39

Trout, Susan W. "Need bulletproof randomization." Fertility and Sterility 80, no. 6 (December 2003): 1535. http://dx.doi.org/10.1016/s0015-0282(03)02224-6.

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40

McDonough, Paul G. "Need bulletproof randomization." Fertility and Sterility 80, no. 6 (December 2003): 1536. http://dx.doi.org/10.1016/s0015-0282(03)02226-x.

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41

Cook, Chad, and Alessandra N. Garcia. "Post-randomization bias." Journal of Manual & Manipulative Therapy 28, no. 2 (March 14, 2020): 69–71. http://dx.doi.org/10.1080/10669817.2020.1739153.

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42

Weksler, Benny. "Time for randomization." Journal of Thoracic and Cardiovascular Surgery 154, no. 2 (August 2017): 712–13. http://dx.doi.org/10.1016/j.jtcvs.2017.03.069.

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43

Lin, Bochao Danae, Yue Li, and Jurjen Luykx. "Mendelian Randomization Concerns." JAMA Psychiatry 75, no. 4 (April 1, 2018): 407. http://dx.doi.org/10.1001/jamapsychiatry.2018.0035.

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44

Abel, U. "Modified replacement randomization." Statistics in Medicine 6, no. 2 (March 1987): 127–35. http://dx.doi.org/10.1002/sim.4780060205.

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45

Schrimpf, Daniel, and Lothar R. Pilz. "Adaptive randomization procedures for the web-based randomization system RANDI2." Int. Journal of Clinical Pharmacology and Therapeutics 50, no. 01 (January 1, 2012): 85–86. http://dx.doi.org/10.5414/cpp50085.

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46

Kaiser, Lee D. "Dynamic randomization and a randomization model for clinical trials data." Statistics in Medicine 31, no. 29 (July 5, 2012): 3858–73. http://dx.doi.org/10.1002/sim.5448.

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47

Melis, René J. F., S. Teerenstra, M. G. M. Olde Rikkert, and G. F. Borm. "Pseudo Cluster Randomization: Balancing the Disadvantages of Cluster and Individual Randomization." Evaluation & the Health Professions 34, no. 2 (May 10, 2010): 151–63. http://dx.doi.org/10.1177/0163278710361925.

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48

Suprun, Maria, and Mayte Suárez-Fariñas. "PlateDesigner: a web-based application for the design of microplate experiments." Bioinformatics 35, no. 9 (October 9, 2018): 1605–7. http://dx.doi.org/10.1093/bioinformatics/bty853.

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Abstract Summary In biological assays, systematic variability, known as a batch effect, can often confound the effects of true biological conditions and has been well documented for a variety of high-throughput technologies. In microplate-based multiplex experiments, such as Luminex or OLINK assays, researchers need to consider both position and plate effects. Those effects can be easily accounted for if the experiments are properly designed, which includes randomization of the samples across multiple experimental runs. However, doing the ad hoc randomization becomes challenging when handling multiple samples. PlateDesigner is the first web-based application that provides randomization for microplate experiments, ensuring that the main principles of the experimental design, such as grouping samples from the same biological units and balancing the distribution of experimental conditions, are applied. Creating randomizations with PlateDesigner is simple and the results can be exported in a variety of formats, and easily integrated with microplate readers and statistical analysis software. Availability and implementation PlateDesigner is written in R/Shiny and is hosted online by the Center of Biostatistics at the Icahn School of Medicine at Mount Sinai. This application is freely available at platedesigner.net.

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49

Bailey, R. A. "Restricted Randomization versus Blocking." International Statistical Review / Revue Internationale de Statistique 53, no. 2 (August 1985): 171. http://dx.doi.org/10.2307/1402933.

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50

Kodish, E., J. D. Lantos, and M. Siegler. "The ethics of randomization." CA: A Cancer Journal for Clinicians 41, no. 3 (May 1, 1991): 180–86. http://dx.doi.org/10.3322/canjclin.41.3.180.

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