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Testing for the multivariate stochastic order among ordered experimental groups with application to dose-response studies.

ABSTRACT: The comparison of two or more ordered experimental groups based on multivariate data is common in a variety of applications such as toxicology, clinical trials and drug development, to name just a few. In this article, we develop a nonparametric methodology for analyzing such data. In particular we propose a global K sample nonparametric test for order among vector valued outcomes. The testing procedure can also be used in a post-hoc fashion to answer questions about the ordering of subgroups and/or single outcomes within any subset of experimental groups. Such a methodology does not currently exist. In contrast with standard methodology such as multivariate analysis of variance (MANOVA), and its nonparametric analogues, we do not assume that the groups differ only by a location parameter or that the components of the response vector have the same marginal distributions between and across groups, that is, we allow for the shape of the distribution to change across groups. We emphasize that our test compares the outcome distributions, not just their mean tendencies, and explicitly incorporates and exploits the order constraints. Consequently it is more powerful than the existing unordered tests. The methodology is illustrated using genotoxicity data where the effect of hydrogen peroxide exposure on damage to DNA is evaluated using a comet assay.

SUBMITTER: Davidov O

PROVIDER: S-EPMC3865181 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Testing for the multivariate stochastic order among ordered experimental groups with application to dose-response studies.

Davidov Ori O Peddada Shyamal S

Biometrics 20131011 4

The comparison of two or more ordered experimental groups based on multivariate data is common in a variety of applications such as toxicology, clinical trials and drug development, to name just a few. In this article, we develop a nonparametric methodology for analyzing such data. In particular we propose a global K sample nonparametric test for order among vector valued outcomes. The testing procedure can also be used in a post-hoc fashion to answer questions about the ordering of subgroups an ...[more]

PMID: 24125397

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Project description:BackgroundLimited options are available for dose-finding clinical trials requiring group-specific dose selection. While conducting parallel trials for groups is an accessible approach to group-specific dose selection, this approach allows for maximum tolerated dose selection that does not align with clinically meaningful group order information.MethodsThe two-stage continual reassessment method is developed for dose-finding in studies involving three or more groups where group frailty order is known between some but not all groups, creating a partial order. This is an extension of the existing continual reassessment method shift model for two ordered groups. This method allows for dose selection by group, where maximum tolerated dose selection follows the known frailty order among groups. For example, if a group is known to be the most frail, the recommended maximum tolerated dose for this group should not exceed the maximum tolerated dose recommended for any other group.ResultsWith limited alternatives for dose-finding in partially ordered groups, this method is compared to two alternatives: (1) an existing method for dose-finding in partially ordered groups which is less computationally accessible and (2) independent trials for each group using the two-stage continual reassessment method. Simulation studies show that when ignoring information on group frailty, using independent continual reassessment method trials by group, 30% of simulations would result in maximum tolerated dose selection that is out of order between groups. In addition, the two-stage continual reassessment method for partially ordered groups selects the maximum tolerated dose more often and assigns more patients to the maximum tolerated dose compared to using independent continual reassessment method trials within each group. Simulation results for the proposed method and the less computationally accessible approach are similar.ConclusionThe proposed continual reassessment method for partially ordered groups ensures appropriate maximum tolerated dose order and improves accuracy of maximum tolerated dose selection, while allowing for trial implementation that is computationally accessible.

Project description:Manual muscle testing (MMT) is a non-invasive assessment tool used by a variety of health care providers to evaluate neuromusculoskeletal integrity, and muscular strength in particular. In one form of MMT called muscle response testing (MRT), muscles are said to be tested, not to evaluate muscular strength, but neural control. One established, but insufficiently validated, application of MRT is to assess a patient's response to semantic stimuli (e.g. spoken lies) during a therapy session. Our primary aim was to estimate the accuracy of MRT to distinguish false from true spoken statements, in randomised and blinded experiments. A secondary aim was to compare MRT accuracy to the accuracy when practitioners used only their intuition to differentiate false from true spoken statements.Two prospective studies of diagnostic test accuracy using MRT to detect lies are presented. A true positive MRT test was one that resulted in a subjective weakening of the muscle following a lie, and a true negative was one that did not result in a subjective weakening of the muscle following a truth. Experiment 2 replicated Experiment 1 using a simplified methodology. In Experiment 1, 48 practitioners were paired with 48 MRT-naïve test patients, forming unique practitioner-test patient pairs. Practitioners were enrolled with any amount of MRT experience. In Experiment 2, 20 unique pairs were enrolled, with test patients being a mix of MRT-naïve and not-MRT-naïve. The primary index test was MRT. A secondary index test was also enacted in which the practitioners made intuitive guesses ("intuition"), without using MRT. The actual verity of the spoken statement was compared to the outcome of both index tests (MRT and Intuition) and their mean overall fractions correct were calculated and reported as mean accuracies.In Experiment 1, MRT accuracy, 0.659 (95% CI 0.623 - 0.695), was found to be significantly different (p?<?0.01) from intuition accuracy, 0.474 (95% CI 0.449 - 0.500), and also from the likelihood of chance (0.500; p?<?0.01). Experiment 2 replicated the findings of Experiment 1. Testing for various factors that may have influenced MRT accuracy failed to detect any correlations.MRT has repeatedly demonstrated significant accuracy for distinguishing lies from truths, compared to both intuition and chance. The primary limitation of this study is its lack of generalisability to other applications of MRT and to MMT.The Australian New Zealand Clinical Trials Registry (ANZCTR; www.anzctr.org.au ; ID # ACTRN12609000455268 , and US-based ClinicalTrials.gov (ID # NCT01066312 ).

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Testing for the multivariate stochastic order among ordered experimental groups with application to dose-response studies.

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Testing for the multivariate stochastic order among ordered experimental groups with application to dose-response studies.

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