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Robust Test (robust + test)

Distribution by Scientific Domains

Life Sciences	47%
Business, Economics, Finance and Accounting	23%

Selected Abstracts

Robust Tests for Single-marker Analysis in Case-Control Genetic Association Studies

ANNALS OF HUMAN GENETICS, Issue 2 2009
Qizhai Li
Summary Choosing an appropriate single-marker association test is critical to the success of case-control genetic association studies. An ideal single-marker analysis should have robust performance across a wide range of potential disease risk models. MAX was designed specifically to achieve such robustness. In this work, we derived the power calculation formula for MAX and conducted a comprehensive power comparison between MAX and two other commonly used single-marker tests, the one-degree-of-freedom (1-df) Cochran-Armitage trend test and the 2-df Pearson ,2 test. We used a single-marker disease risk model and a two-marker haplotype risk model to explore the performances of the above three tests. We found that each test has its own "sweet" spots. Among the three tests considered, MAX appears to have the most robust performance. [source]

Two-Stage Group Sequential Robust Tests in Family-Based Association Studies: Controlling Type I Error

ANNALS OF HUMAN GENETICS, Issue 4 2008
Lihan K. Yan
Summary In family-based association studies, an optimal test statistic with asymptotic normal distribution is available when the underlying genetic model is known (e.g., recessive, additive, multiplicative, or dominant). In practice, however, genetic models for many complex diseases are usually unknown. Using a single test statistic optimal for one genetic model may lose substantial power when the model is mis-specified. When a family of genetic models is scientifically plausible, the maximum of several tests, each optimal for a specific genetic model, is robust against the model mis-specification. This robust test is preferred over a single optimal test. Recently, cost-effective group sequential approaches have been introduced to genetic studies. The group sequential approach allows interim analyses and has been applied to many test statistics, but not to the maximum statistic. When the group sequential method is applied, type I error should be controlled. We propose and compare several approaches of controlling type I error rates when group sequential analysis is conducted with the maximum test for family-based candidate-gene association studies. For a two-stage group sequential robust procedure with a single interim analysis, two critical values for the maximum tests are provided based on a given alpha spending function to control the desired overall type I error. [source]

Robustness of alternative non-linearity tests for SETAR models

JOURNAL OF FORECASTING, Issue 3 2004
Wai-Sum Chan
Abstract In recent years there has been a growing interest in exploiting potential forecast gains from the non-linear structure of self-exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR-type non-linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non-linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non-linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR-type non-linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Application of the distributed activation energy model to biomass and biomass constituents devolatilization

AICHE JOURNAL, Issue 10 2009
María V. Navarro
Abstract In this study, an investigation about the thermal behavior of four different woods was carried out. The distributed activation energy model was applied to study the effect of heating rate on the reaction of single solids. Results obtained were used in the curve prediction of fraction of mass remaining and rate of mass loss vs. temperature at more realistic heating rates. The possible calculation of biomass samples behavior in pyrolysis conditions as the summation of their constituents, lignin, cellulose, and hemi-cellulose is also explored. All the samples show a weak interaction between the constituents which produce slight differences between experimental and calculated behavior. However, differences between experimental and calculated data lower than 2% offer a robust test of the applicability of the model on kinetic studies of a wide range of biomass samples, heating rates, data input format and equipment layout. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]

Free Radical Bulk Polymerization of Styrene: Simulation of Molecular Weight Distributions to High Conversion Using Experimentally Obtained Rate Coefficients

MACROMOLECULAR THEORY AND SIMULATIONS, Issue 6 2003
Per B. Zetterlund
Abstract Previously obtained experimental conversion-dependences of the propagation rate coefficient (kp), the termination rate coefficient (kt) and the initiator efficiency (f) for the free-radical bulk polymerization of styrene at 70,°C have been used to simulate the full molecular weight distributions (MWD) to high conversion using the software package PREDICI, providing a robust test of the kinetic model adopted. Satisfactory agreement with the experimental MWD's (GPC) was obtained up to approximately 70% conversion. Beyond 70% conversion, the high MW shoulder that appears was correctly predicted, although the amount of such polymer was somewhat underestimated. This discrepancy is believed to probably have its origin in experimental error in the conversion-dependences of kp, kt and f, in particular kt, that were employed in the simulations, rather than indicate a more fundamental short-coming of the model employed. [source]

MOND plus classical neutrinos are not enough for cluster lensing

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2008
Priyamvada Natarajan
ABSTRACT Clusters of galaxies offer a robust test bed for probing the nature of dark matter that is insensitive to the assumption of the gravity theories. Both Modified Newtonian Dynamics (MOND) and General Relativity (GR) would require similar amounts of non-baryonic matter in clusters as MOND boosts the gravity only mildly on cluster scales. Gravitational lensing allows us to estimate the enclosed mass in clusters on small (,20,50 kpc) and large (,several 100 kpc) scales independent of the assumptions of equilibrium. Here, we show for the first time that a combination of strong and weak gravitational lensing effects can set interesting limits on the phase-space density of dark matter in the centres of clusters. The phase-space densities derived from lensing observations are inconsistent with neutrino masses ranging from 2,7 eV, and hence do not support the 2 eV-range particles required by MOND. To survive, the most plausible modification for MOND may be an additional degree of dynamical freedom in a covariant incarnation. [source]

UK DEBT SUSTAINABILITY: SOME NONLINEAR EVIDENCE AND THEORETICAL IMPLICATIONS,

THE MANCHESTER SCHOOL, Issue 3 2008
JOHN CONSIDINE
In this paper we assess whether the UK public finances were sustainable for the period 1919,2001. A robust test of sustainability is presented using a nonlinear representation of the debt,GDP ratio. Empirical evidence supports debt sustainability. Moreover, the exponential smooth transition autoregressive representation is evidence that sustainability is the result of active debt management rather than tax smoothing. The results strongly support the active debt management hypothesis for the UK. [source]

Genotypic Association Analysis Using Discordant-Relative-Pairs

ANNALS OF HUMAN GENETICS, Issue 1 2009
T. Yan
Summary In practice, family-based design has been widely used in disease-gene association analysis. The major advantage of such design is that it is not subject to spurious association due to population structure such as population stratification (PS) and admixture. A disadvantage is that parental genotypes are hard to obtain if the disease is late onset for which a discordant-relative-pair design is useful. Designs of such kind include full-sib-pair, half-sib-pair, first-cousin-pair, and so on. The closer the relatedness of the pair, the less possible that they are subject to population stratification. On the other hand, the association test using close relative-pairs may be less powerful due to over-matching. Trade-off between these two factors (population structure and over-matching) is the major concern of this study. Some tests, namely McNemar's test, matched Cochran-Armitage trend tests (CATTs), matched maximum efficient robust test (MERT), and Bhapkar's test, are used for testing disease-gene association based on relative-pair designs. These tests are shown to be valid in the presence of PS but not admixture. Numerical studies show that the McNemar's test, additive CATT, MERT, and Bhapkar's test are robust in power, but none of them is uniformly more powerful than the others. In most simulations, the power of any of the tests increases as the pair is more distant. The proposed methods are applied to two real examples. [source]

Two-Stage Group Sequential Robust Tests in Family-Based Association Studies: Controlling Type I Error

Phylogeny of the sea spiders (Arthropoda, Pycnogonida) based on direct optimization of six loci and morphology

CLADISTICS, Issue 3 2007
Claudia P. Arango
Higher-level phylogenetics of Pycnogonida has been discussed for many decades but scarcely studied from a cladistic perspective. Traditional taxonomic classifications are yet to be tested and affinities among families and genera are not well understood. Pycnogonida includes more than 1300 species described, but no systematic revisions at any level are available. Previous attempts to propose a phylogeny of the sea spiders were limited in characters and taxon sampling, therefore not allowing a robust test of relationships among lineages. Herein, we present the first comprehensive phylogenetic analysis of the Pycnogonida based on a total evidence approach and Direct Optimization. Sixty-three pycnogonid species representing all families including fossil taxa were included. For most of the extant taxa more than 6 kb of nuclear and mitochondrial DNA and 78 morphological characters were scored. The most parsimonious hypotheses obtained in equally weighted total evidence analyses show the two most diverse families Ammotheidae and Callipallenidae to be non-monophyletic. Austrodecidae + Colossendeidae + Pycnogonidae are in the basal most clade, these are morphologically diverse groups of species mostly found in cold waters. The raising of the family Pallenopsidae is supported, while Eurycyde and Ascorhynchus are definitely separated from Ammotheidae. The four fossil taxa are grouped within living Pycnogonida, instead of being an early derived clade. This phylogeny represents a solid framework to work towards the understanding of pycnogonid systematics, providing a data set and a testable hypothesis that indicate those clades that need severe testing, especially some of the deep nodes of the pycnogonid tree and the relationships of ammotheid and callipallenid forms. The inclusion of more rare taxa and additional sources of evidence are necessary for a phylogenetic classification of the Pycnogonida. © The Willi Hennig Society 2006. [source]

Identifying Welfare Effects from Subjective Questions

ECONOMICA, Issue 271 2001
Martin Ravallion
We argue that the welfare inferences drawn from answers to subjective,qualitative survey questions are clouded by concerns over the structure of measurement errors and how latent psychological factors influence observed respondent characteristics. We propose a panel data model that allows more robust tests and we estimate the model on a high-quality survey for Russia. We find significant income effects on an individual's subjective economic welfare. Demographic effects are weak at given income per capita. Ill-health and becoming unemployed lower welfare at given current income, although the unemployment effect is not robust, and returning to work does not restore welfare without an income gain. [source]

Genome-wide association studies for discrete traits

GENETIC EPIDEMIOLOGY, Issue S1 2009
Duncan C. Thomas
Abstract Genome-wide association studies of discrete traits generally use simple methods of analysis based on ,2 tests for contingency tables or logistic regression, at least for an initial scan of the entire genome. Nevertheless, more power might be obtained by using various methods that analyze multiple markers in combination. Methods based on sliding windows, wavelets, Bayesian shrinkage, or penalized likelihood methods, among others, were explored by various participants of Genetic Analysis Workshop 16 Group 1 to combine information across multiple markers within a region, while others used Bayesian variable selection methods for genome-wide multivariate analyses of all markers simultaneously. Imputation can be used to fill in missing markers on individual subjects within a study or in a meta-analysis of studies using different panels. Although multiple imputation theoretically should give more robust tests of association, one participant contribution found little difference between results of single and multiple imputation. Careful control of population stratification is essential, and two contributions found that previously reported associations with two genes disappeared after more precise control. Other issues considered by this group included subgroup analysis, gene-gene interactions, and the use of biomarkers. Genet. Epidemiol. 33 (Suppl. 1):S8,S12, 2009. © 2009 Wiley-Liss, Inc. [source]

Compensation Dispersion Between and Within Hierarchical Levels

JOURNAL OF ECONOMICS & MANAGEMENT STRATEGY, Issue 1 2007
Pedro Ortín-Ángel
This paper studies the dispersion around the expected compensation of workers before and after controlling for hierarchical positions in cross-section data samples. From data for Spanish managers, we find that this dispersion decreases with education and work experience before entering the current job and increases with job tenure. This finding contrasts with previous research that finds a positive association between compensation dispersion and education and work experience. We explain the new finding through a model of learning that separates compensation dispersion between jobs and within jobs (hierarchical positions). The model takes advantage of the information revealed when workers are promoted to their current hierarchical positions and allows for more robust tests of learning theories. [source]

The chronology of abrupt climate change and Late Upper Palaeolithic human adaptation in Europe,

JOURNAL OF QUATERNARY SCIENCE, Issue 5 2006
S. P. E. Blockley
Abstract This paper addresses the possible connections between the onset of human expansion in Europe following the Last Glacial Maximum, and the timing of abrupt climate warming at the onset of the Lateglacial (Bölling/Allerød) Interstadial. There are opposing views as to whether or not human populations and activities were directly ,forced' by climate change, based on different comparisons between archaeological and environmental data. We review the geochronological assumptions and approaches on which data comparisons have been attempted in the past, and argue that the uncertainties presently associated with age models based on calibrated radiocarbon dates preclude robust testing of the competing models, particularly when comparing the data to non-radiocarbon-based timescales such as the Greenland ice core records. The paper concludes with some suggestions as to the steps that will be necessary if more robust tests of the models are to be developed in the future. Copyright © 2006 John Wiley & Sons, Ltd. [source]

DOES DIVING LIMIT BRAIN SIZE IN CETACEANS?

MARINE MAMMAL SCIENCE, Issue 2 2006
Lori Marino
Abstract We test the longstanding hypothesis, known as the dive constraint hypothesis, that the oxygenation demands of diving pose a constraint on aquatic mammal brain size.Using a sample of 23 cetacean species we examine the relationship among six different measures of relative brain size, body size, and maximum diving duration. Unlike previous tests we include body size as a covariate and perform independent contrast analyses to control for phylogeny. We show that diving does not limit brain size in cetaceans and therefore provide no support for the dive constraint hypothesis. Instead, body size is the main predictor of maximum diving duration in cetaceans. Furthermore, our findings show that it is important to conduct robust tests of evolutionary hypotheses by employing a variety of measures of the dependent variable, in this case, relative brain size. [source]

Robust Quantitative Trait Association Tests in the Parent-Offspring Triad Design: Conditional Likelihood-Based Approaches

ANNALS OF HUMAN GENETICS, Issue 2 2009
J.-Y. Wang
Summary Association studies, based on either population data or familial data, have been widely applied to mapping of genes underlying complex diseases. In family-based association studies, using case-parent triad families, the popularly used transmission/disequilibrium test (TDT) was proposed for avoidance of spurious association results caused by other confounders such as population stratification. Originally, the TDT was developed for analysis of binary disease data. Extending it to allow for quantitative trait analysis of complex diseases and for robust analysis of binary diseases against the uncertainty of mode of inheritance has been thoroughly discussed. Nevertheless, studies on robust analysis of quantitative traits for complex diseases received relatively less attention. In this paper, we use parent-offspring triad families to demonstrate the feasibility of establishment of the robust candidate-gene association tests for quantitative traits. We first introduce the score statistics from the conditional likelihoods based on parent-offspring triad data under various genetic models. By applying two existing robust procedures we then construct the robust association tests for analysis of quantitative traits. Simulations are conducted to evaluate empirical type I error rates and powers of the proposed robust tests. The results show that these robust association tests do exhibit robustness against the effect of misspecification of the underlying genetic model on testing powers. [source]

A Robust Genome-Wide Scan Statistic of the Wellcome Trust Case,Control Consortium

BIOMETRICS, Issue 4 2009
Jungnam Joo
Summary In genome-wide association (GWA) studies, test statistics that are efficient and robust across various genetic models are preferable, particularly for studying multiple diseases in the Wellcome Trust Case,Control Consortium (WTCCC, 2007,,Nature,447, 661,678). A new test statistic, the minimum of the p-values of the trend test and Pearson's test, was considered by the WTCCC. It is referred to here as MIN2. Because the minimum of two p-values is no longer a valid p-value itself, the WTCCC only used it to rank single nucleotide polymorphisms (SNPs) but did not report the p-values of the associated SNPs when MIN2 was used for ranking. Given its importance in practice, we derive the asymptotic null distribution of MIN2, study some of its analytical properties related to GWA studies, and compare it with existing methods (the trend test, Pearson's test, MAX3, and the constrained likelihood ratio test [CLRT]) by simulations across a wide range of possible genetic models: the recessive (REC), additive (ADD), multiplicative (MUL), dominant (DOM), and overdominant models. The results show that MAX3 and CLRT have greater efficiency robustness than other tests when the REC, ADD/MUL, and DOM models are possible, whereas Pearson's test and MIN2 have greater efficiency robustness if the possible genetic models also include the overdominant model. We conclude that robust tests (MAX3, MIN2, CLRT, and Pearson's test) are preferable to a single trend test for initial GWA studies. The four robust tests are applied to more than 100 SNPs associated with 11 common diseases identified by the two WTCCC GWA studies. [source]