Rejection Graph for Multiple Testing of Elliptical Model for Market Network

2018 ◽  
pp. 221-234
Author(s):  
D. P. Semenov ◽  
Petr A. Koldanov
Keyword(s):  
Multiple Testing ◽  
Elliptical Model

MULTIPLE TESTING OF SIGN SYMMETRY FOR STOCK RETURN DISTRIBUTIONS

2016 ◽  
Vol 19 (08) ◽  
pp. 1650049 ◽  
Author(s):  
PETR KOLDANOV ◽  
NINA LOZGACHEVA
Keyword(s):  
Stock Returns ◽  
Multiple Testing ◽  
Stock Return ◽  
Testing Procedure ◽  
Multiple Testing Procedure ◽  
Elliptical Model ◽  
Return Distributions ◽  
Real Market ◽  
High Degree ◽  
Uniformly Most Powerful

Multiple statistical procedure for testing elliptical model for stock returns distribution is proposed. Sign symmetry conditions are chosen as individual hypotheses for multiple testing. Distribution free uniformly most powerful tests of Neyman structure are constructed for individual hypotheses testing. Associated stepwise multiple testing procedure is applied for the real market data. Numerical experiments shows that hypothesis of elliptical model is rejected. At the same time it is observed that the graph of rejected individual hypotheses has unexpected structure. Namely, this graph is sparse and has a few hubs of high degree. Removing this hubs leads to nonrejection of hypothesis of elliptical model.

scholarly journals Genetic biomarkers in the VEGF pathway predicting response to anti-VEGF therapy in age-related macular degeneration

2019 ◽  
Vol 4 (1) ◽  
pp. e000273
Author(s):  
Irina Balikova ◽  
Laurence Postelmans ◽  
Brigitte Pasteels ◽  
Pascale Coquelet ◽  
Janet Catherine ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Macular Degeneration ◽  
Treatment Response ◽  
Multiple Testing ◽  
Age Related Macular Degeneration ◽  
Patient Specific ◽  
Multiple Testing Correction ◽  
Anti Vegf ◽  
Age Related ◽  
Vegf Pathway

ObjectiveAge-related macular degeneration (ARMD) is a leading cause of visual impairment. Intravitreal injections of anti-vascular endothelial growth factor (VEGF) are the standard treatment for wet ARMD. There is however, variability in patient responses, suggesting patient-specific factors influencing drug efficacy. We tested whether single nucleotide polymorphisms (SNPs) in genes encoding VEGF pathway members contribute to therapy response.Methods and analysisA retrospective cohort of 281 European wet ARMD patients treated with anti-VEGF was genotyped for 138 tagging SNPs in the VEGF pathway. Per patient, we collected best corrected visual acuity at baseline, after three loading injections and at 12 months. We also registered the injection number and changes in retinal morphology after three loading injections (central foveal thickness (CFT), intraretinal cysts and serous neuroepithelium detachment). Changes in CFT after 3 months were our primary outcome measure. Association of SNPs to response was assessed by binomial logistic regression. Replication was attempted by associating visual acuity changes to genotypes in an independent Japanese cohort.ResultsAssociation with treatment response was detected for seven SNPs, including in FLT4 (rs55667289: OR=0.746, 95% CI 0.63 to 0.88, p=0.0005) and KDR (rs7691507: OR=1.056, 95% CI 1.02 to 1.10, p=0.005; and rs2305945: OR=0.963, 95% CI 0.93 to 1.00, p=0.0472). Only association with rs55667289 in FLT4 survived multiple testing correction. This SNP was unavailable for testing in the replication cohort. Of six SNPs tested for replication, one was significant although not after multiple testing correction.ConclusionIdentifying genetic variants that define treatment response can help to develop individualised therapeutic approaches for wet ARMD patients and may point towards new targets in non-responders.

scholarly journals Multitrait genetic association analysis identifies 50 new risk loci for gastro-oesophageal reflux, seven new loci for Barrett’s oesophagus and provides insights into clinical heterogeneity in reflux diagnosis

Gut ◽  
2021 ◽  
pp. gutjnl-2020-323906
Author(s):  
Jue-Sheng Ong ◽  
Jiyuan An ◽  
Xikun Han ◽  
Matthew H Law ◽  
Priyanka Nandakumar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Testing ◽  
Association Studies ◽  
Barrett’S Oesophagus ◽  
Oesophageal Reflux ◽  
Oesophageal Adenocarcinoma ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Disease Heterogeneity ◽  
Barrett's Oesophagus

ObjectiveGastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett’s oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications.DesignWe applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA).ResultsWe identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA.ConclusionOur multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.

scholarly journals 2dFDR: a new approach to confounder adjustment substantially increases detection power in omics association studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sangyoon Yi ◽  
Xianyang Zhang ◽  
Lu Yang ◽  
Jinyan Huang ◽  
Yuanhang Liu ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Statistical Power ◽  
Association Studies ◽  
Control Procedure ◽  
Multiple Testing Correction ◽  
New Approach ◽  
False Discovery ◽  
Traditional Procedure ◽  
Extensive Evaluation ◽  
Confounder Adjustment

AbstractOne challenge facing omics association studies is the loss of statistical power when adjusting for confounders and multiple testing. The traditional statistical procedure involves fitting a confounder-adjusted regression model for each omics feature, followed by multiple testing correction. Here we show that the traditional procedure is not optimal and present a new approach, 2dFDR, a two-dimensional false discovery rate control procedure, for powerful confounder adjustment in multiple testing. Through extensive evaluation, we demonstrate that 2dFDR is more powerful than the traditional procedure, and in the presence of strong confounding and weak signals, the power improvement could be more than 100%.

scholarly journals Framework for identifying drug repurposing candidates from observational healthcare data

JAMIA Open ◽  
2020 ◽  
Author(s):  
Michal Ozery-Flato ◽  
Yaara Goldschmidt ◽  
Oded Shaham ◽  
Sivan Ravid ◽  
Chen Yanover
Keyword(s):  
Causal Inference ◽  
Observational Data ◽  
Prescription Drugs ◽  
Domain Knowledge ◽  
Multiple Testing ◽  
Statistical Significance ◽  
Drug Effects ◽  
Drug Repurposing ◽  
Design Parameters ◽  
Medical Databases

Abstract Objective Observational medical databases, such as electronic health records and insurance claims, track the healthcare trajectory of millions of individuals. These databases provide real-world longitudinal information on large cohorts of patients and their medication prescription history. We present an easy-to-customize framework that systematically analyzes such databases to identify new indications for on-market prescription drugs. Materials and Methods Our framework provides an interface for defining study design parameters and extracting patient cohorts, disease-related outcomes, and potential confounders in observational databases. It then applies causal inference methodology to emulate hundreds of randomized controlled trials (RCTs) for prescribed drugs, while adjusting for confounding and selection biases. After correcting for multiple testing, it outputs the estimated effects and their statistical significance in each database. Results We demonstrate the utility of the framework in a case study of Parkinson’s disease (PD) and evaluate the effect of 259 drugs on various PD progression measures in two observational medical databases, covering more than 150 million patients. The results of these emulated trials reveal remarkable agreement between the two databases for the most promising candidates. Discussion Estimating drug effects from observational data is challenging due to data biases and noise. To tackle this challenge, we integrate causal inference methodology with domain knowledge and compare the estimated effects in two separate databases. Conclusion Our framework enables systematic search for drug repurposing candidates by emulating RCTs using observational data. The high level of agreement between separate databases strongly supports the identified effects.

scholarly journals The Romano–Wolf multiple-hypothesis correction in Stata

2020 ◽  
Vol 20 (4) ◽  
pp. 812-843
Author(s):  
Damian Clarke ◽  
Joseph P. Romano ◽  
Michael Wolf
Keyword(s):  
Error Rate ◽  
Multiple Testing ◽  
Original Data ◽  
Dependence Structure ◽  
Familywise Error Rate ◽  
Testing Procedures ◽  
Multiple Testing Procedures ◽  
Multiple Hypothesis ◽  
Wide Range ◽  
Performance Gains

When considering multiple-hypothesis tests simultaneously, standard statistical techniques will lead to overrejection of null hypotheses unless the multiplicity of the testing framework is explicitly considered. In this article, we discuss the Romano–Wolf multiple-hypothesis correction and document its implementation in Stata. The Romano–Wolf correction (asymptotically) controls the familywise error rate, that is, the probability of rejecting at least one true null hypothesis among a family of hypotheses under test. This correction is considerably more powerful than earlier multiple-testing procedures, such as the Bonferroni and Holm corrections, given that it takes into account the dependence structure of the test statistics by resampling from the original data. We describe a command, rwolf, that implements this correction and provide several examples based on a wide range of models. We document and discuss the performance gains from using rwolf over other multiple-testing procedures that control the familywise error rate.

Renal Sodium Handling in Relation to Environmental and Genetic Factors in Untreated Chinese

2020 ◽  
Author(s):  
Yuan-Yuan Kang ◽  
Yi-Bang Cheng ◽  
Qian-Hui Guo ◽  
Chang-Sheng Sheng ◽  
Qi-Fang Huang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Multiple Testing ◽  
Genetic Factors ◽  
Blood Pressure Monitoring ◽  
Lithium Concentration ◽  
Tubular Dysfunction ◽  
Renal Tubular Dysfunction ◽  
Renal Sodium Handling ◽  
Renal Tubular ◽  
Sodium Handling

Abstract Background We investigated proximal and distal renal tubular sodium handling, as assessed by fractional excretion of lithium (FELi) and fractional distal reabsorption rate of sodium (FDRNa), in relation to environmental and genetic factors in untreated patients. Methods Our study participants were suspected hypertensive patients being off antihypertensive medication for ≥2 weeks and referred for 24-hour ambulatory blood pressure monitoring. We collected serum and 24-hour urine for measurement of sodium, creatinine and lithium concentration, and calculated FELi and FDRNa. We genotyped 19 SNPs associated with renal sodium handling or blood pressure using the ABI SNapShot method. Results The 1409 participants (664 men, 47.1%) had a mean (±SD) age of 51.0±10.5 years. After adjustment for host factors, both FELi and FDRNa were significantly (P≤0.01) associated with season and humidity, explaining ~1.3% and ~3.5% of the variance, respectively. FELi was highest in autumn and lowest in summer and intermediate in spring and winter (P=0.007). FDRNa was also highest in autumn but lowest in winter and intermediate in spring and summer (P<0.001). Neither FELi nor FDRNa was associated with outdoor temperature or atmospheric pressure (P≥0.13). After adjustment for host and environmental factors and Bonferroni multiple testing, among the 19 studied genetic variants, only rs12513375 was significantly associated with FELi and FDRNa (P≤0.004) and explained about 1.7% of the variance. Conclusions Renal sodium handling as measured by endogenous lithium clearance was sensitive to major environmental and genetic factors. Our finding is towards the use of these indexes for the definition of renal tubular dysfunction.

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