Multivariate permutation tests for two sample testing in presence of nondetects with application to microarray data

Arboretti, Rosa; Bathke, Arne C.; Pesarin, Fortunato; Salmaso, Luigi

doi:10.1177/0962280219832225

Cited by 4 publications

(4 citation statements)

References 38 publications

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“…The numerous properties that characterize this multivariate and multistratum methodology make it very flexible and widely applicable in various research contexts, including in the medical (endocrinological, hepatological, chronic intestinal diseases, etc.) and health (feeding, physical activity, disability, and epidemiology) fields [ 32 , 33 , 34 ]: It is free from normality and homoscedasticity assumptions [ 35 ]; It can be effectively used even in the presence of small samples or in the presence of missing data [ 36 , 37 ]; It deals with variables of nominal, ordinal, and numerical nature without the need to identify the dependence structure among variables [ 38 , 39 ]; It allows for stratified analyses in which confounding factors can be isolated [ 40 ]; …”

Section: Methodsmentioning

confidence: 99%

“…It can be effectively used even in the presence of small samples or in the presence of missing data [ 36 , 37 ];…”

Section: Methodsmentioning

confidence: 99%

“…-It is free from normality and homoscedasticity assumptions [35]; -It can be effectively used even in the presence of small samples or in the presence of missing data [36,37]; -It deals with variables of nominal, ordinal, and numerical nature without the need to identify the dependence structure among variables [38,39]; -It allows for stratified analyses in which confounding factors can be isolated [40];…”

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confidence: 99%

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The Influence of Food Regimes on Oxidative Stress: A Permutation-Based Approach Using the NPC Test

et al. 2023

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(1) Background: This paper aims to assess the existence of significant differences between two dietary regimes (omnivorous vs. semi-vegetarian) with reference to some oxidative stress markers (SOD, GPx, TRxR, GR, AGEs, and AOPPs) using non-parametric combination methodology based on a permutation test. (2) Methods: At the endocrinology unit of Messina University Hospital, two hundred subjects were asked to fill out a questionnaire about their dietary habits. None were under any pharmacological treatment. Using the NPC test, all comparisons were performed stratifying patients according to gender, age (≤40 or >40 years), BMI (normal weight vs. overweight), physical activity (sedentary vs. active lifestyle), TSH, FT4 levels in quartiles, and diagnosis of Hashimoto’s thyroiditis. We evaluated differences in oxidative stress parameters in relation to two examined dietary regimes (omnivorous vs. semi-vegetarian). (3) Results: The antioxidant parameters GPx and TRxR were significantly lower in subjects with an omnivorous diet than in semi-vegetarians, particularly in females, both age groups, subjects with normal weight, those not affected by Hashimoto’s thyroiditis, and both the sedentary and active lifestyle groups. Finally, the AGE and AOPP markers were significantly lower in semi-vegetarians. (4) Conclusion: Thanks to the NPC methodology, we can state that dietary patterns exert a significant influence on some oxidative stress parameters.

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Section: Methodsmentioning

confidence: 99%

“…It can be effectively used even in the presence of small samples or in the presence of missing data [ 36 , 37 ];…”

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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The Influence of Food Regimes on Oxidative Stress: A Permutation-Based Approach Using the NPC Test

et al. 2023

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“…NPC is characterized by some properties that make it preferable to other approaches of classical inference [ 33 ]: the assumptions of normality and homoscedasticity are not required [ 36 ]; the analyzed variables can be of any nature (nominal, ordinal, and numerical); it can be applied even when there are missing data [ 37 ]; it guarantees statistical power even in presence of low sampling size [ 38 ]; tackles problems of multivariate hypothesis testing without the need to specify the dependence structure among variables [ 39 , 40 ]; it offers the possibility of stratified analyses with respect to a confounding factor [ 41 ]; it allows to verify restricted alternative hypotheses (stochastic ordering) [ 35 ]; it can be applied even when the number of observed subjects is smaller than the number of variables [ 42 ]. …”

Section: Methodsmentioning

confidence: 99%

Non-Motherhood between Obligation and Choice: Statistical Analysis Based on Permutation Tests of Spontaneous and Induced Abortion Rates in the Italian Context

et al. 2022

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(1) Background: This paper aims to examine two relevant phenomena in the context of public health: spontaneous abortion (SA) and induced abortion (IA). SA is one of the most common complications of pregnancies; IA is a conscious choice that is made by the mother/couple. (2) Methods: Permutation tests were applied to SA and IA standardized rates detected by ISTAT (2016–2020). The NPC test, chosen for its optimal properties, was applied to compare different Italian territorial divisions (stratifying for year and age classes of women) and analyze the trend of years by stochastic ordering. (3) Results: Only for SA, there are significant differences among the three territorial divisions: the South records higher SA standardized rates than the North and the Center; the rates of IA are similar. Relating to distinct women age classes, the SA standardized rates do not show significant differences among the three analyzed geographical areas; different results are highlighted for IA. Stochastic ordering shows that only the IA standardized rates are characterized by a significant monotonous decreasing trend over the years. (4) Conclusion: The SA phenomenon has shown a decreasing trend that could be justified by the progress of science. For IA, we can certainly say that the general decrease in the phenomenon is due to the greater use of contraceptive methods that help to prevent unwanted pregnancies.

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Nonparametric Analysis of Multivariate Data in Factorial Designs with Nondetects: A Case Study with Microbiome Data

Kiefel,

Freidl

2024

JABES

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The term “nondetects” describes observations that are not fully observed because the true value is below a detection threshold—and can therefore not be precisely detected. One may also consider them a special case of left-censored data. Nondetects occur frequently, for instance, in life sciences research in medicine or microbiology. This article examines the use of nonparametric inference methods for multivariate data in factorial designs in situations where nondetects are present, and it evaluates their performance. The focus is on testing hypotheses regarding interaction and main factor effects. The nonparametric centerpiece of the methodology is assuming the nonparametric relative effect (probabilistic index) and its generalizations as the functional on which inference is built, along with the respective invariance properties of the resulting tests. On this basis, we apply and evaluate recently proposed nonparametric analogs to the following types of multivariate test statistics: (1) Wald-type statistic (WTS), (2) ANOVA-type statistic (ATS), (3) Lawley–Hotelling trace, (4) Wilks Lambda (Likelihood ratio), (5) Bartlett–Nanda–Pillai trace. Except for the WTS, all the mentioned methods are available through the R-package nparmd. Extensive simulations and a case study from the field of microbiology demonstrate that the proposed methods can handle commonly occurring rates of nondetects without substantial impairment of specificity and sensitivity.

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Multivariate permutation tests for two sample testing in presence of nondetects with application to microarray data

Cited by 4 publications

References 38 publications

The Influence of Food Regimes on Oxidative Stress: A Permutation-Based Approach Using the NPC Test

The Influence of Food Regimes on Oxidative Stress: A Permutation-Based Approach Using the NPC Test

Non-Motherhood between Obligation and Choice: Statistical Analysis Based on Permutation Tests of Spontaneous and Induced Abortion Rates in the Italian Context

Nonparametric Analysis of Multivariate Data in Factorial Designs with Nondetects: A Case Study with Microbiome Data

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