ORCID Profile
0000-0002-0247-5136
Current Organisation
UNSW Sydney
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Publisher: Wiley
Date: 23-02-2016
DOI: 10.1002/SIM.6909
Abstract: Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the s le size for single-step and step-wise procedures. These are implemented in our R package rPowerS leSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute s le sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd.
Publisher: Public Library of Science (PLoS)
Date: 08-08-2017
Publisher: Wiley
Date: 11-03-2013
DOI: 10.1111/NMO.12078
Abstract: The probiotic fermented milk (PFM) containing Bifidobacterium lactis CNCM I-2494 improved gastrointestinal (GI) well-being and digestive symptoms in a previous trial involving women reporting minor digestive symptoms. Our objective is to confirm these findings in a second study and in a pooled analysis of both studies. In this double-blind, controlled, parallel design study, subjects without diagnosed GI disorders consumed PFM or control dairy product daily for 4 weeks. Endpoints comprised weekly assessment of GI well-being (primary endpoint), rate of responders and digestive symptoms. Data were analyzed on full analysis set population (n = 324) and on the pooled data of randomized subjects of this study with those of the first study (n = 538). In this second study, no significant difference was observed in the percentage of women reporting an improvement in GI well-being [OR = 1.20 (95% CI 0.87, 1.66)] and rate of responders [OR = 1.38 (95% CI 0.89, 2.14)]. Composite score of digestive symptoms was significantly (P < 0.05) reduced in PFM when compared to the control group [LSmean = -0.42 (95% CI -0.81, -0.03)]. In the pooled analysis, significant differences were observed in favor of PFM group for all endpoints: percentage of women with improved GI well-being [OR = 1.36 (95% CI 1.07, 1.73)], rate of responders [OR = 1.53 (95% CI 1.09, 2.16)] and composite score of digestive symptoms [LSmean = -0.48 (95% CI -0.80, -0.16)]. This second study did not confirm improvement on the primary endpoint. However, a pooled analysis of the two trials showed improvement in GI well-being and digestive symptoms in women reporting minor digestive symptoms.
Publisher: Elsevier BV
Date: 04-2010
Publisher: American Society of Neuroradiology (ASNR)
Date: 05-07-2012
DOI: 10.3174/AJNR.A3174
Publisher: Informa UK Limited
Date: 2013
Publisher: Wiley
Date: 27-03-2013
DOI: 10.1111/JTSA.12026
Publisher: MDPI AG
Date: 16-10-2021
DOI: 10.3390/MATH9202605
Abstract: In this paper, we complement a study recently conducted in a paper of H.A. Mombeni, B. Masouri and M.R. Akhoond by introducing five new asymmetric kernel c.d.f. estimators on the half-line [0,∞), namely the Gamma, inverse Gamma, LogNormal, inverse Gaussian and reciprocal inverse Gaussian kernel c.d.f. estimators. For these five new estimators, we prove the asymptotic normality and we find asymptotic expressions for the following quantities: bias, variance, mean squared error and mean integrated squared error. A numerical study then compares the performance of the five new c.d.f. estimators against traditional methods and the Birnbaum–Saunders and Weibull kernel c.d.f. estimators from Mombeni, Masouri and Akhoond. By using the same experimental design, we show that the LogNormal and Birnbaum–Saunders kernel c.d.f. estimators perform the best overall, while the other asymmetric kernel estimators are sometimes better but always at least competitive against the boundary kernel method from C. Tenreiro.
Publisher: Informa UK Limited
Date: 22-04-2020
Publisher: Informa UK Limited
Date: 09-2007
DOI: 10.1080/02643290701617330
Abstract: We investigated the visual word recognition ability of M.T., a young boy with surface dyslexia, by means of a paradigm that measures performance as a function of the eye fixation position within the word, known as the "viewing-position effect" paradigm. In well-achieving readers, the viewing-position effect is mainly determined by factors affecting letter visibility and by lexical constraints on word recognition. We further quantified M.T.'s sensory limitations on letter visibility by computing visual-span profiles - that is, the number of letters recognizable at a glance. Finally, in an ideal-observer's perspective, M.T.'s performance was compared with a parameter-free model combining M.T.'s letter visibility data with a simple lexical matching rule. The results showed that M.T. did not use the whole visual information available on letter identities to recognize words and that preorthographical factors constrained his word recognition performance. The results can be best accounted for by a reduction of the number of letters processed in parallel.
Publisher: Informa UK Limited
Date: 17-08-2020
Publisher: Informa UK Limited
Date: 04-03-2014
DOI: 10.1080/10543406.2013.860156
Abstract: The use of two or more primary correlated endpoints is becoming increasingly common. A mandatory approach when analyzing data from such clinical trials is to control the family-wise error rate (FWER). In this context, we provide formulas for computation of s le size and for data analysis. Two approaches are discussed: an in idual method based on a union-intersection procedure and a global procedure, based on a multivariate model that can take into account adjustment variables. These methods are illustrated with simulation studies and applications. An R package known as rPowerS leSize is also available.
Publisher: Institute of Mathematical Statistics
Date: 2019
DOI: 10.1214/19-SS125
Publisher: Informa UK Limited
Date: 25-07-2022
Publisher: MDPI AG
Date: 03-10-2021
DOI: 10.3390/JRFM14100467
Abstract: There are many real-world situations in which complex interacting forces are best described by a series of equations. Traditional regression approaches to these situations involve modeling and estimating each in idual equation (producing estimates of “partial derivatives”) and then solving the entire system for reduced form relationships (“total derivatives”). We examine three estimation methods that produce “total derivative estimates” without having to model and estimate each separate equation. These methods produce a unique total derivative estimate for every observation, where the differences in these estimates are produced by omitted variables. A plot of these estimates over time shows how the estimated relationship has evolved over time due to omitted variables. A moving 95% confidence interval (constructed like a moving average) means that there is only a five percent chance that the next total derivative would lie outside that confidence interval if the recent variability of omitted variables does not increase. Simulations show that two of these methods produce much less error than ignoring the omitted variables problem does when the importance of omitted variables noticeably exceeds random error. In an ex le, the spread rate of COVID-19 is estimated for Brazil, Europe, South Africa, the UK, and the USA.
Publisher: Elsevier BV
Date: 2017
Publisher: Informa UK Limited
Date: 21-12-2017
Publisher: Foundation for Open Access Statistic
Date: 2016
Publisher: Wiley
Date: 03-2008
DOI: 10.1111/J.1460-9568.2008.06123.X
Abstract: A central question in chemical senses is the way that odorant molecules are represented in the brain. To date, many studies, when taken together, suggest that structural features of the molecules are represented through a spatio-temporal pattern of activation in the olfactory bulb (OB), in both glomerular and mitral cell layers. Mitral/tufted cells interact with a large population of inhibitory interneurons resulting in a temporal patterning of bulbar local field potential (LFP) activity. We investigated the possibility that molecular features could determine the temporal pattern of LFP oscillatory activity in the OB. For this purpose, we recorded the LFPs in the OB of urethane-anesthetized, freely breathing rats in response to series of aliphatic odorants varying subtly in carbon-chain length or functional group. In concordance with our previous reports, we found that odors evoked oscillatory activity in the LFP signal in both the beta and gamma frequency bands. Analysis of LFP oscillations revealed that, although molecular features have almost no influence on the intrinsic characteristics of LFP oscillations, they influence the temporal patterning of bulbar oscillations. Alcohol family odors rarely evoke gamma oscillations, whereas ester family odors rather induce oscillatory patterns showing beta/gamma alternation. Moreover, for molecules with the same functional group, the probability of gamma occurrence is correlated to the vapor pressure of the odor. The significance of the relation between odorant features and oscillatory regimes along with their functional relevance are discussed.
Publisher: Elsevier BV
Date: 08-2005
Publisher: Elsevier BV
Date: 10-2007
Publisher: Elsevier BV
Date: 04-2011
DOI: 10.1016/J.NEUROIMAGE.2011.01.013
Abstract: R is a language and environment for statistical computing and graphics. It can be considered an alternative implementation of the S language developed in the 1970s and 1980s for data analysis and graphics (Becker and Chambers, 1984 Becker et al., 1988). The R language is part of the GNU project and offers versions that compile and run on almost every major operating system currently available. We highlight several R packages built specifically for the analysis of neuroimaging data in the context of functional MRI, diffusion tensor imaging, and dynamic contrast-enhanced MRI. We review their methodology and give an overview of their capabilities for neuroimaging. In addition we summarize some of the current activities in the area of neuroimaging software development in R.
Publisher: Springer Science and Business Media LLC
Date: 21-09-2014
Publisher: Elsevier BV
Date: 07-2020
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 05-2012
Publisher: Informa UK Limited
Date: 05-2009
Publisher: Elsevier BV
Date: 11-2023
Publisher: Springer Science and Business Media LLC
Date: 06-09-2016
DOI: 10.1038/SREP32760
Abstract: This study examined the heritability of brain grey matter structures in a subs le of older adult twins (93 MZ and 68 DZ twin pairs mean age 70 years) from the Older Australian Twins Study. The heritability estimates of subcortical regions ranged from 0.41 (amygdala) to 0.73 (hippoc us), and of cortical regions, from 0.55 (parietal lobe) to 0.78 (frontal lobe). Corresponding structures in the two hemispheres were influenced by the same genetic factors and high genetic correlations were observed between the two hemispheric regions. There were three genetically correlated clusters, comprising (i) the cortical lobes (frontal, temporal, parietal and occipital lobes) (ii) the basal ganglia (caudate, putamen and pallidum) with weak genetic correlations with cortical lobes, and (iii) the amygdala, hippoc us, thalamus and nucleus accumbens grouped together, which genetically correlated with both basal ganglia and cortical lobes, albeit relatively weakly. Our study demonstrates a complex but patterned and clustered genetic architecture of the human brain, with ergent genetic determinants of cortical and subcortical structures, in particular the basal ganglia.
Publisher: Springer Science and Business Media LLC
Date: 24-09-2021
Publisher: Foundation for Open Access Statistic
Date: 2011
Publisher: Walter de Gruyter GmbH
Date: 2021
Abstract: We present a general methodology to construct triplewise independent sequences of random variables having a common but arbitrary marginal distribution F (satisfying very mild conditions). For two specific sequences, we obtain in closed form the asymptotic distribution of the s le mean. It is non-Gaussian (and depends on the specific choice of F ). This allows us to illustrate the extent of the ‘failure’ of the classical central limit theorem (CLT) under triplewise independence. Our methodology is simple and can also be used to create, for any integer K , new K -tuplewise independent sequences that are not mutually independent. For K [four.tf], it appears that the sequences created using our methodology do verify a CLT, and we explain heuristically why this is the case.
Publisher: Elsevier BV
Date: 07-2009
Publisher: Foundation for Open Access Statistic
Date: 2015
Publisher: Wiley
Date: 06-07-2016
DOI: 10.1002/CJS.11292
Publisher: Elsevier BV
Date: 11-2018
Publisher: Informa UK Limited
Date: 02-09-2020
Publisher: Oxford University Press (OUP)
Date: 10-09-2015
DOI: 10.1093/BIOINFORMATICS/BTV535
Abstract: Motivation: The association between two blocks of ‘omics’ data brings challenging issues in computational biology due to their size and complexity. Here, we focus on a class of multivariate statistical methods called partial least square (PLS). Sparse version of PLS (sPLS) operates integration of two datasets while simultaneously selecting the contributing variables. However, these methods do not take into account the important structural or group effects due to the relationship between markers among biological pathways. Hence, considering the predefined groups of markers (e.g. genesets), this could improve the relevance and the efficacy of the PLS approach. Results: We propose two PLS extensions called group PLS (gPLS) and sparse gPLS (sgPLS). Our algorithm enables to study the relationship between two different types of omics data (e.g. SNP and gene expression) or between an omics dataset and multivariate phenotypes (e.g. cytokine secretion). We demonstrate the good performance of gPLS and sgPLS compared with the sPLS in the context of grouped data. Then, these methods are compared through an HIV therapeutic vaccine trial. Our approaches provide parsimonious models to reveal the relationship between gene abundance and the immunological response to the vaccine. Availability and implementation: The approach is implemented in a comprehensive R package called sgPLS available on the CRAN. Contact: b.liquet@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
Publisher: Informa UK Limited
Date: 24-11-2022
Publisher: Wiley
Date: 05-2004
No related grants have been discovered for Pierre Lafaye de Micheaux.