Probabilistic Index Models

Thas, Olivier; Neve, Jan De; Clement, Lieven; Ottoy, Jean–Pierre

doi:10.1111/j.1467-9868.2011.01020.x

Cited by 119 publications

(162 citation statements)

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“…In this paper we situate a large class of rank tests within the semiparametric Probabilistic Index Model (PIM) framework of Thas et al (2012). This model can be seen as the rank-equivalent of the GLM, but not to be confused with the rank-transform approach of Conover and Iman (1981).…”

Section: Introductionmentioning

confidence: 99%

“…This probability is known as the probabilistic index (PI); see, for example Acion et al (2006); Thas et al (2012) and the references therein. The distributions F i and F j may depend on p-dimensional regressor patterns, say X i and X j .…”

Section: Introductionmentioning

confidence: 99%

“…For a general Z ij and g(·), Thas et al (2012) provide a semiparametric consistent and asymptotically normally distributed estimator of β and a consistent sandwich estimator of its asymptotic variance. They primarily consider Z ij = X j −X i together with the logit and probit link function.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, by embedding the method in the PIM framework we can relate the tests to parameters with a well defined interpretation on population level. The full connection between a PIM and rank tests were not exploited in Thas et al (2012) since specific parametrizations are required. More specifically, depending on this parametrization, we establish a simple connection between the PIM and the WMW, KW, Friedman (Friedman, 1937), Mack-Skillings (MS) (Mack and Skillings, 1980), Brown-Hettmansperger (BH) (Brown and Hettmansperger, 2002) and the Jonckheere-Terpstra (JT) (Jonckheere, 1954;Terpstra, 1952) rank tests and some tests proposed by Brunner and Puri (2001) based on the work of Akritas and Arnold (1994).…”

Section: Introductionmentioning

confidence: 99%

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A Regression Framework for Rank Tests Based on the Probabilistic Index Model

Neve

Thas²

2015

Journal of the American Statistical Association

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We demonstrate how many classical rank tests, such as the Wilcoxon-MannWhitney, Kruskal-Wallis and Friedman test, can be embedded in a statistical modelling framework and how the method can be used to construct new rank tests. In addition to hypothesis testing, the method allows for estimating effect sizes with an informative interpretation, resulting in a better understanding of the data. Supplementary materials for this article are available online.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Regression Framework for Rank Tests Based on the Probabilistic Index Model

Neve

Thas²

2015

Journal of the American Statistical Association

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“…To avoid strong (parametric) distributional assumptions, the alternatives are formulated using probabilities that pairs or triples of observations coming from different groups are in a specific order of magnitude. The interesting probabilities are called probabilistic indices (PI), see also Thas, De Neve, Clement, and Ottoy (2012). The test statistics are based on natural estimates of these PIs, that is, the corresponding two and several sample U-statistics.…”

Section: Introductionmentioning

confidence: 99%

Mann-Whitney Type Tests for Microarray Experiments: TheRPackagegMWT

Fischer¹,

Oja²

2015

J. Stat. Soft.

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We present the R package gMWT which is designed for the comparison of several treatments (or groups) for a large number of variables. The comparisons are made using certain probabilistic indices (PI). The PIs computed here tell how often pairs or triples of observations coming from different groups appear in a specific order of magnitude. Classical two and several sample rank test statistics such as the Mann-Whitney-Wilcoxon, Kruskal-Wallis, or Jonckheere-Terpstra test statistics are simple functions of these PI. Also new test statistics for directional alternatives are provided. The package gMWT can be used to calculate the variable-wise PI estimates, to illustrate their multivariate distribution and mutual dependence with joint scatterplot matrices, and to construct several classical and new rank tests based on the PIs. The aim of the paper is first to briefly explain the theory that is necessary to understand the behavior of the estimated PIs and the rank tests based on them. Second, the use of the package is described and illustrated with simulated and real data examples. It is stressed that the package provides a new flexible toolbox to analyze large gene or microRNA expression data sets, collected on microarrays or by other high-throughput technologies. The testing procedures can be used in an eQTL analysis, for example, as implemented in the package GeneticTools.

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Endovascular Thrombectomy for Large Ischemic Stroke Across Ischemic Injury and Penumbra Profiles

Sarraj,

Hassan,

Abraham

et al. 2024

JAMA

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ImportanceWhether endovascular thrombectomy (EVT) efficacy for patients with acute ischemic stroke and large cores varies depending on the extent of ischemic injury is uncertain.ObjectiveTo describe the relationship between imaging estimates of irreversibly injured brain (core) and at-risk regions (mismatch) and clinical outcomes and EVT treatment effect.Design, Setting, and ParticipantsAn exploratory analysis of the SELECT2 trial, which randomized 352 adults (18-85 years) with acute ischemic stroke due to occlusion of the internal carotid or middle cerebral artery (M1 segment) and large ischemic core to EVT vs medical management (MM), across 31 global centers between October 2019 and September 2022.InterventionEVT vs MM.Main Outcomes and MeasuresPrimary outcome was functional outcome—90-day mRS score (0, no symptoms, to 6, death) assessed by adjusted generalized OR (aGenOR; values &gt;1 represent more favorable outcomes). Benefit of EVT vs MM was assessed across levels of ischemic injury defined by noncontrast CT using ASPECTS score and by the volume of brain with severely reduced blood flow on CT perfusion or restricted diffusion on MRI.ResultsAmong 352 patients randomized, 336 were analyzed (median age, 67 years; 139 [41.4%] female); of these, 168 (50%) were randomized to EVT, and 2 additional crossover MM patients received EVT. In an ordinal analysis of mRS at 90 days, EVT improved functional outcomes compared with MM within ASPECTS categories of 3 (aGenOR, 1.71 [95% CI, 1.04-2.81]), 4 (aGenOR, 2.01 [95% CI, 1.19-3.40]), and 5 (aGenOR, 1.85 [95% CI, 1.22-2.79]). Across strata for CT perfusion/MRI ischemic core volumes, aGenOR for EVT vs MM was 1.63 (95% CI, 1.23-2.16) for volumes ≥70 mL, 1.41 (95% CI, 0.99-2.02) for ≥100 mL, and 1.47 (95% CI, 0.84-2.56) for ≥150 mL. In the EVT group, outcomes worsened as ASPECTS decreased (aGenOR, 0.91 [95% CI, 0.82-1.00] per 1-point decrease) and as CT perfusion/MRI ischemic core volume increased (aGenOR, 0.92 [95% CI, 0.89-0.95] per 10-mL increase). No heterogeneity of EVT treatment effect was observed with or without mismatch, although few patients without mismatch were enrolled.Conclusion and RelevanceIn this exploratory analysis of a randomized clinical trial of patients with extensive ischemic stroke, EVT improved clinical outcomes across a wide spectrum of infarct volumes, although enrollment of patients with minimal penumbra volume was low. In EVT-treated patients, clinical outcomes worsened as presenting ischemic injury estimates increased.Trial RegistrationClinicalTrials.gov Identifier: NCT03876457

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Probabilistic Index Models

Cited by 119 publications

References 98 publications

A Regression Framework for Rank Tests Based on the Probabilistic Index Model

A Regression Framework for Rank Tests Based on the Probabilistic Index Model

Mann-Whitney Type Tests for Microarray Experiments: TheRPackagegMWT

Endovascular Thrombectomy for Large Ischemic Stroke Across Ischemic Injury and Penumbra Profiles

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