scholarly journals Combining Dependent P-values with an Empirical Adaptation of Brown's Method

2015 ◽  
Author(s):  
William Poole ◽  
David L. Gibbs ◽  
Ilya Shmulevich ◽  
Brady Bernard ◽  
Theo Knijnenburg

Combining P-values from multiple statistical tests is a common exercise in bioinformatics. However, this procedure is non-trivial for dependent P-values. Here we discuss an empirical adaptation of Brown's Method (an extension of Fisher's Method) for combining dependent P-values which is appropriate for the correlated data sets found in high-throughput biological experiments. We show that Fisher's Method is biased when used on dependent sets of P-values with both simulated data and gene expression data from The Cancer Genome Atlas (TCGA). When applied on the same data sets, the Empirical Brown's Method provides a better null distribution and a more conservative result. The Empirical Brown's Method is available in Python, R, and MATLAB and can be obtained from https://github.com/IlyaLab/CombiningDependentPvaluesUsingEBM.

2021 ◽  
Author(s):  
Paulo S.P. Silveira ◽  
Joaquim E. Vieira ◽  
Alexandre A. Ferraro ◽  
Jose O. Siqueira

Abstract Background: Bland and Altman plot method is a widely cited graphical approach to assess equivalence of quantitative measurement techniques. Perhaps due to its graphical output, it has been widely applied, however often misinterpreted by lacking of inferential statistical support. To compare data sets obtained from two measurement techniques, researchers may apply Pearson’s correlation, ordinal least-square linear regression, or the Bland-Altman plot methods, failing to locate the weakness of each measurement technique. We aim to develop and distribute a statistical method in R in order to add robust and suitable inferential statistics of equivalence. Methods: Three nested tests based on structural regressions are proposed to assess the equivalence of structural means (accuracy), equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements of data pairs obtained from the same subject) to reach statistical support for the equivalence of measurement techniques. Graphical outputs illustrating these three tests were added to follow Bland and Altman’s principles of easy communication. Results: Statistical p-values and robust approach by bootstrapping with corresponding graphs provide objective, robust measures of equivalence. Five pairs of data sets were analyzed in order to criticize previously published articles that applied the Bland and Altman’s principles, thus showing the suitability of the present statistical approach. In one case it was demonstrated strict equivalence, three cases showed partial equivalence, and one case showed poor equivalence. Package containing open codes and data is available with installation instructions on SourceForge for free distribution. Conclusions: Statistical p-values and robust approach assess the equivalence of accuracy, precision, and agreement for measurement techniques. Decomposition in three tests helps the location of any disagreement as a means to fix a new technique.


1989 ◽  
Vol 46 (10) ◽  
pp. 1831-1838 ◽  
Author(s):  
Keith R. Thompson ◽  
Fred H. Page

Synchrony of recruitment to distinct fish stocks is difficult to detect because the available time series are generally short and autocorrelated. The recent introduction of more sophisticated statistical techniques has not been particularly helpful; several contradictory interpretations of similar data sets are discussed in the paper. To help resolve the continuing controversy surrounding the question of synchrony, we review three statistical tests of independence and determine their power using simulated data. The tests are then applied to recruitment data for six cod (Gadus morhua) and three haddock (Melanogrammus aeglefinus) stocks of the northwest Atlantic. Prior to analysis each series was first-differenced to reduce autocorrelation and hence increase statistical reliability in the results. The cod stocks are shown to fluctuate independently of the haddock stocks. There is, however, evidence of synchrony for stocks of the same species; the more widely separated cod stocks have a lower mean correlation [Formula: see text] than the haddock [Formula: see text] but both correlations are significant at the 1% level. The within-species synchrony is not due to fluctuations in our index of egg production and it appears that environmental forcing is probably important.


2020 ◽  
Vol 132 (6) ◽  
pp. 1970-1976
Author(s):  
Ashwin G. Ramayya ◽  
H. Isaac Chen ◽  
Paul J. Marcotte ◽  
Steven Brem ◽  
Eric L. Zager ◽  
...  

OBJECTIVEAlthough it is known that intersurgeon variability in offering elective surgery can have major consequences for patient morbidity and healthcare spending, data addressing variability within neurosurgery are scarce. The authors performed a prospective peer review study of randomly selected neurosurgery cases in order to assess the extent of consensus regarding the decision to offer elective surgery among attending neurosurgeons across one large academic institution.METHODSAll consecutive patients who had undergone standard inpatient surgical interventions of 1 of 4 types (craniotomy for tumor [CFT], nonacute redo CFT, first-time spine surgery with/without instrumentation, and nonacute redo spine surgery with/without instrumentation) during the period 2015–2017 were retrospectively enrolled (n = 9156 patient surgeries, n = 80 randomly selected individual cases, n = 20 index cases of each type randomly selected for review). The selected cases were scored by attending neurosurgeons using a need for surgery (NFS) score based on clinical data (patient demographics, preoperative notes, radiology reports, and operative notes; n = 616 independent case reviews). Attending neurosurgeon reviewers were blinded as to performing provider and surgical outcome. Aggregate NFS scores across various categories were measured. The authors employed a repeated-measures mixed ANOVA model with autoregressive variance structure to compute omnibus statistical tests across the various surgery types. Interrater reliability (IRR) was measured using Cohen’s kappa based on binary NFS scores.RESULTSOverall, the authors found that most of the neurosurgical procedures studied were rated as “indicated” by blinded attending neurosurgeons (mean NFS = 88.3, all p values < 0.001) with greater agreement among neurosurgeon raters than expected by chance (IRR = 81.78%, p = 0.016). Redo surgery had lower NFS scores and IRR scores than first-time surgery, both for craniotomy and spine surgery (ANOVA, all p values < 0.01). Spine surgeries with fusion had lower NFS scores than spine surgeries without fusion procedures (p < 0.01).CONCLUSIONSThere was general agreement among neurosurgeons in terms of indication for surgery; however, revision surgery of all types and spine surgery with fusion procedures had the lowest amount of decision consensus. These results should guide efforts aimed at reducing unnecessary variability in surgical practice with the goal of effective allocation of healthcare resources to advance the value paradigm in neurosurgery.


2019 ◽  
Vol 45 (9) ◽  
pp. 1183-1198
Author(s):  
Gaurav S. Chauhan ◽  
Pradip Banerjee

Purpose Recent papers on target capital structure show that debt ratio seems to vary widely in space and time, implying that the functional specifications of target debt ratios are of little empirical use. Further, target behavior cannot be adjudged correctly using debt ratios, as they could revert due to mechanical reasons. The purpose of this paper is to develop an alternative testing strategy to test the target capital structure. Design/methodology/approach The authors make use of a major “shock” to the debt ratios as an event and think of a subsequent reversion as a movement toward a mean or target debt ratio. By doing this, the authors no longer need to identify target debt ratios as a function of firm-specific variables or any other rigid functional form. Findings Similar to the broad empirical evidence in developed economies, there is no perceptible and systematic mean reversion by Indian firms. However, unlike developed countries, proportionate usage of debt to finance firms’ marginal financing deficits is extensive; equity is used rather sparingly. Research limitations/implications The trade-off theory could be convincingly refuted at least for the emerging market of India. The paper here stimulated further research on finding reasons for specific financing behavior of emerging market firms. Practical implications The results show that the firms’ financing choices are not only depending on their own firm’s specific variables but also on the financial markets in which they operate. Originality/value This study attempts to assess mean reversion in debt ratios in a unique but reassuring manner. The results are confirmed by extensive calibration of the testing strategy using simulated data sets.


2020 ◽  
Vol 12 ◽  
pp. 175883592097711
Author(s):  
Xia Ran ◽  
Jinyuan Xiao ◽  
Yi Zhang ◽  
Huajing Teng ◽  
Fang Cheng ◽  
...  

Background: Intratumor heterogeneity (ITH) has been shown to be inversely associated with immune infiltration in several cancers including clear cell renal cell carcinoma (ccRCC), but it remains unclear whether ITH is associated with response to immunotherapy (e.g. PD-1 blockade) in ccRCC. Methods: We quantified ITH using mutant-allele tumor heterogeneity, investigated the association of ITH with immune parameters in patients with ccRCC ( n = 336) as well as those with papillary RCC (pRCC, n = 280) from The Cancer Genome Atlas, and validations were conducted in patients with ccRCC from an independent cohort ( n = 152). The relationship between ITH and response to anti-PD-1 immunotherapy was explored in patients with metastatic ccRCC from a clinical trial of anti-PD-1 therapy ( n = 35), and validated in three equal-size simulated data sets ( n = 60) generated by random sampling with replacement based on this clinical trial cohort. Results: In ccRCC, low ITH was associated with better survival, more reductions in tumor burden, and clinical benefit of anti-PD-1 immunotherapy through modulating immune activity involving more neoantigens, elevated expression of HLA class I genes, and higher abundance of dendritic cells. Furthermore, we found that the association between the level of ITH and response to PD-1 blockade was independent of the mutation status of PBRM1 and that integrating both factors performed better than the individual predictors in predicting the benefit of anti-PD-1 immunotherapy in ccRCC patients. In pRCC, increased immune activity was also observed in low- versus high-ITH tumors, including higher neoantigen counts, increased abundance of monocytes, and decreased expression of PD-L1 and PD-L2. Conclusions: ITH may be helpful in the identification of patients who could benefit from PD-1 blockade in ccRCC, and even in pRCC where no genomic metrics has been found to correlate with response to immune checkpoint inhibitors.


Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 949
Author(s):  
Jiangyi Wang ◽  
Min Liu ◽  
Xinwu Zeng ◽  
Xiaoqiang Hua

Convolutional neural networks have powerful performances in many visual tasks because of their hierarchical structures and powerful feature extraction capabilities. SPD (symmetric positive definition) matrix is paid attention to in visual classification, because it has excellent ability to learn proper statistical representation and distinguish samples with different information. In this paper, a deep neural network signal detection method based on spectral convolution features is proposed. In this method, local features extracted from convolutional neural network are used to construct the SPD matrix, and a deep learning algorithm for the SPD matrix is used to detect target signals. Feature maps extracted by two kinds of convolutional neural network models are applied in this study. Based on this method, signal detection has become a binary classification problem of signals in samples. In order to prove the availability and superiority of this method, simulated and semi-physical simulated data sets are used. The results show that, under low SCR (signal-to-clutter ratio), compared with the spectral signal detection method based on the deep neural network, this method can obtain a gain of 0.5–2 dB on simulated data sets and semi-physical simulated data sets.


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