Factor Analysis for Multiple Testing (FAMT): An R Package for Large-Scale Signi
Journal of Statistical Software, 2011 The R package FAMT (factor analysis for multiple testing) provides a powerful method for large-scale significance testing under dependence. It is especially designed to select differentially expressed genes in microarray data when the correlation ...
David Causeur +3 more
doaj +1 more source
Cycle Threshold Values in the Context of Multiple RT-PCR Testing for SARS-CoV-2 [PDF]
, 2021 Purpose: Discharge or follow up of confirmed coronavirus disease 2019 (COVID-19) cases depend on accurate interpretation of RT-PCR. Currently, positive/negative interpretations are based on amplification instead of quantification of cycle threshold (Ct ...
Espin, Emilia +10 more
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Toxocara infection in the differential diagnosis of multiple sclerosis in the Middle East [PDF]
, 2020 A critical step in the diagnosis of multiple sclerosis is to rule out a heterogeneous variety of multiple sclerosis mimickers, which is crucial in the era of powerful immune-modulator treatments.
El Najjar, Mayssam +3 more
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Design considerations for a Multiple Sclerosis Fatigue mobile app MS Energize: A pragmatic iterative approach using usability testing and resonance checks. [PDF]
, 2021 Multiple sclerosis (MS) is a chronic neurological condition affecting around 2.2 million people worldwide. The illness includes a range of symptoms, with fatigue considered to be one of the most disabling.
Thomas, P. +6 more
core +1 more source
Nonparametric Inference for Multivariate Data: The R Package npmv
Journal of Statistical Software, 2017 We introduce the R package npmv that performs nonparametric inference for the comparison of multivariate data samples and provides the results in easy-to-understand, but statistically correct, language.
Woodrow W. Burchett +3 more
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Erratum regarding “Optimizing effective numbers of tests by vine copula modeling”
Dependence Modeling, 2020 We correct the definition of the family-wise error rate in our previous article “Optimizing effective numbers of tests by vine copula modeling”.
Steffen Nico, Dickhaus Thorsten
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Computationally efficient permutation-based confidence interval estimation for tail-area FDR
Frontiers in Genetics, 2013 Challenges of satisfying parametric assumptions in genomic settings with thousands or millions of tests have led investigators to combine powerful False Discovery Rate (FDR) approaches with computationally expensive but exact permutation testing.
Joshua eMillstein, Dmitri eVolfson
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Generation of address sequences with a given switching activity
Informatika, 2020 The relevance of testing modern computing systems and, first of all, their storage devices is shown. The studies are based on the use of a universal method for generating the address sequences with desired properties for multiple March tests of ...
V. N. Yarmolik, N. A. Shevchenko
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Optimizing effective numbers of tests by vine copula modeling
Dependence Modeling, 2020 In the multiple testing context, we utilize vine copulae for optimizing the effective number of tests. It is well known that for the calibration of multiple tests for control of the family-wise error rate the dependencies between the marginal tests are ...
Steffen Nico, Dickhaus Thorsten
doaj +1 more source
On multiple portmanteau tests* [PDF]
Journal of Time Series Analysis, 2009 Abstract. The portmanteau statistic based on the firstmresidual autocorrelations is used for diagnostic checks on the adequacy of fitting a model with varyingm. In this article, we propose an approximation of the joint probability of multiple portmanteau tests with different degrees of freedom (DF).
openaire +2 more sources