New Bayesian approaches to equivalence testing

2021 ◽  
pp. 1-17
Author(s):  
Josimara Tatiane da Silva ◽  
Juliana Cobre ◽  
Mário de Castro
Keyword(s):  
Equivalence Testing ◽  
Bayesian Approaches

PrePrint - Exploring Perceptions of Meaningful Relationships

2018 ◽  
Author(s):  
Nataly Beribisky ◽  
Heather Davidson ◽  
Rob Cribbie
Keyword(s):  
Effect Size ◽  
Mean Difference ◽  
Practical Significance ◽  
Equivalence Testing ◽  
Significant Variability ◽  
Meaningful Relationship ◽  
Meaningful Relationships ◽  
Context Free

Researchers often need to consider the practical significance of a relationship. For example, interpreting the magnitude of an effect size or establishing bounds in equivalence testing requires knowledge of the meaningfulness of a relationship. However, there has been little research exploring the degree of relationship among variables (e.g., correlation, mean difference) necessary for an association to be interpreted as meaningful or practically significant. In this study, we presented statistically trained and untrained participants with a collection of figures that displayed varying degrees of mean difference between groups or correlations among variables and participants indicated whether or not each relationship was meaningful. The results suggest that statistically trained and untrained participants differ in their qualification of a meaningful relationship, and that there is significant variability in how large a relationship must be before it is labeled meaningful. The results also shed some light on what degree of relationship is considered meaningful by individuals in a context-free setting.

Comparing Intensive English Program (IEP) and Directly-Admitted International Students’ Academic Achievement

2020 ◽  
Author(s):  
Anthony Schmidt
Keyword(s):  
Higher Education ◽  
International Students ◽  
Equivalence Testing ◽  
Intensive English ◽  
Intensive English Program ◽  
Student Groups ◽  
First Semester ◽  
Intensive English Programs ◽  
Statistical Equivalence ◽  
Direct Admission

Intensive English programs (IEPs) exist as an additional pathway into higher education for international students who need additional language support before full matriculation. Despite their long history in higher education, there is little research on the effectiveness of these programs. The current research examines the effectiveness of an IEP by comparing IEP students to directly-admitted international students. Results from regression models on first-semester and first-year GPA indicated no significant differences between these two student groups. Follow-up equivalence testing indicated statistical equivalence in several cases. The findings lead to the conclusion that the IEP is effective in helping students perform on par with directly-admitted international students. These findings imply further support for IEPs and alterative pathways to direct admission.

scholarly journals Bayesian graphical models for modern biological applications

2021 ◽  
Author(s):  
Yang Ni ◽  
Veerabhadran Baladandayuthapani ◽  
Marina Vannucci ◽  
Francesco C. Stingo
Keyword(s):  
Graphical Models ◽  
Cancer Genomics ◽  
Graph Structure ◽  
Biological Processes ◽  
Limited Sample ◽  
Large Networks ◽  
Bayesian Approaches ◽  
Complex Sampling ◽  
Complex Dependence ◽  
Bayesian Graphical Models

AbstractGraphical models are powerful tools that are regularly used to investigate complex dependence structures in high-throughput biomedical datasets. They allow for holistic, systems-level view of the various biological processes, for intuitive and rigorous understanding and interpretations. In the context of large networks, Bayesian approaches are particularly suitable because it encourages sparsity of the graphs, incorporate prior information, and most importantly account for uncertainty in the graph structure. These features are particularly important in applications with limited sample size, including genomics and imaging studies. In this paper, we review several recently developed techniques for the analysis of large networks under non-standard settings, including but not limited to, multiple graphs for data observed from multiple related subgroups, graphical regression approaches used for the analysis of networks that change with covariates, and other complex sampling and structural settings. We also illustrate the practical utility of some of these methods using examples in cancer genomics and neuroimaging.

scholarly journals Equivalence Testing for Regression Discontinuity Designs

2020 ◽  
pp. 1-17
Author(s):  
Erin Hartman
Keyword(s):  
Political Science ◽  
Current Practice ◽  
Regression Discontinuity ◽  
Regression Function ◽  
Superior Performance ◽  
Equivalence Testing ◽  
Simulation Studies ◽  
Equivalence Tests ◽  
Regression Discontinuity Designs ◽  
Testing Approach

Abstract Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to argue the design is credible. These tests, one for continuity in the regression function for a pretreatment covariate, and one for continuity in the density of the forcing variable, use a null of no difference in the parameter of interest at the discontinuity. Common practice can, incorrectly, conflate a failure to reject evidence of a flawed design with evidence that the design is credible. The well-known equivalence testing approach addresses these problems, but how to implement equivalence tests in the RD framework is not straightforward. This paper develops two equivalence tests tailored for RD designs that allow researchers to provide statistical evidence that the design is credible. Simulation studies show the superior performance of equivalence-based tests over tests-of-difference, as used in current practice. The tests are applied to the close elections RD data presented in Eggers et al. (2015b).

Strategy to equivalence testing for development and scale up of biopharmaceutical downstream processes

2021 ◽  
Vol 235 ◽  
pp. 116497
Author(s):  
Christina Yassouridis ◽  
Astrid Dürauer ◽  
Theresa Scharl ◽  
Friedrich Leisch ◽  
Cécile Brocard ◽  
...  
Keyword(s):  
Scale Up ◽  
Equivalence Testing ◽  
Downstream Processes

scholarly journals MET: a Java package for fast molecule equivalence testing

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Jördis-Ann Schüler ◽  
Steffen Rechner ◽  
Matthias Müller-Hannemann
Keyword(s):  
Chemical Properties ◽  
Graph Isomorphism ◽  
Isomorphism Problem ◽  
Equivalence Classes ◽  
Equivalence Testing ◽  
Equivalence Test ◽  
Graph Isomorphism Problem ◽  
2D Structure ◽  
Node Labels ◽  
Labelled Graphs

AbstractAn important task in cheminformatics is to test whether two molecules are equivalent with respect to their 2D structure. Mathematically, this amounts to solving the graph isomorphism problem for labelled graphs. In this paper, we present an approach which exploits chemical properties and the local neighbourhood of atoms to define highly distinctive node labels. These characteristic labels are the key for clever partitioning molecules into molecule equivalence classes and an effective equivalence test. Based on extensive computational experiments, we show that our algorithm is significantly faster than existing implementations within , and . We provide our Java implementation as an easy-to-use, open-source package (via GitHub) which is compatible with . It fully supports the distinction of different isotopes and molecules with radicals.

scholarly journals Association between Migraine and the Risk of Stroke: A Bayesian Meta-Analysis

2021 ◽  
Vol 13 (7) ◽  
pp. 3759
Author(s):  
Kim-Ngan Ta-Thi ◽  
Kai-Jen Chuang ◽  
Chyi-Huey Bai
Keyword(s):  
Ischemic Stroke ◽  
Hemorrhagic Stroke ◽  
Stroke Risk ◽  
Meta Analysis ◽  
Credible Interval ◽  
Fixed Effect Model ◽  
Bayesian Approaches ◽  
Effect Model ◽  
Newcastle Ottawa Scale ◽  
Form Quality

There are still inconsistent results about association between migraine and stroke risk in studies. This paper was to review findings on the association between migraine (with or without aura) and stroke risk. We searched articles in the Embase and PubMed up to January 2021. Two independent reviewers extracted basic data from individual studies using a standardized form. Quality of studies was also assessed using the Newcastle–Ottawa Scale. We conducted a meta-analysis, both classical and Bayesian approaches. We identified 17 eligible studies with a sample size more than 2,788,000 participants. In the fixed effect model, the results demonstrated that migraine was positively associated with the risk of total stroke, hemorrhagic stroke, and ischemic stroke. Nevertheless, migraine was associated with only total stroke in the random effects model (risk ratio (RR) 1.31, 95%CI: 1.06–1.62). The probability that migraine increased total stroke risk was 0.978 (RR 1.31; 95% credible interval (CrI): 1.01–1.72). All types of migraine were not associated with ischemic stroke and hemorrhagic stroke. Under three prior distributions, there was no association between migraine and the risk of ischemic stroke or hemorrhagic stroke. Under the non-informative prior and enthusiastic prior, there was a high probability that migraine was associated with total stroke risk.

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