Stepwise multiple testing as formalized data snooping

It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

Cerebrospinal fluid in the diagnosis of multiple sclerosis: a consensus report.

The Committee of the European Concerted Action for Multiple Sclerosis (Charcot Foundation) organised five workshops to discuss CSF analytical standards in the diagnosis of multiple sclerosis. This consensus report from 12 European countries summarises the results of those workshops. It is hoped that neurologists will confer with their colleagues in clinical chemistry to arrange the best possible local practice. The most sensitive method for the detection of oligoclonal immunoglobulin bands is isoelectric focusing. The same amounts of IgG in parallel CSF and serum samples are used and oligoclonal bands are revealed with IgG specific antibody staining. All laboratories performing isoelectric focusing should check their technique at least annually using "blind" standards for the five different CSF and serum patterns. Quantitative measurements of IgG production in the CNS are less sensitive than isoelectric focusing. The preferred method for detection of blood-CSF barrier dysfunction is the albumin quotient. The CSF albumin or total protein concentrations are less satisfactory. These results must be interpreted with reference to the age of the patient and the local method of determination. Cells should be counted. The normal value is no more than 4 cells/microliters. Among evolving optional tests, measurement of the combined local synthesis of antibodies against measles, rubella, and/or varicella zoster could represent a significant advance if it offers higher specificity (not sensitivity) for identifying chronic rather than acute inflammation. Other tests that may have useful correlations with clinical indices include those for oligoclonal free light chains, IgM, IgA, or myelin basic protein concentrations.

Improving the sensitivity of the sequence profile method.

The sequence profile method (Gribskov M, McLachlan AD, Eisenberg D, 1987, Proc Natl Acad Sci USA 84:4355-4358) is a powerful tool to detect distant relationships between amino acid sequences. A profile is a table of position-specific scores and gap penalties, providing a generalized description of a protein motif, which can be used for sequence alignments and database searches instead of an individual sequence. A sequence profile is derived from a multiple sequence alignment. We have found 2 ways to improve the sensitivity of sequence profiles: (1) Sequence weights: Usage of individual weights for each sequence avoids bias toward closely related sequences. These weights are automatically assigned based on the distance of the sequences using a published procedure (Sibbald PR, Argos P, 1990, J Mol Biol 216:813-818). (2) Amino acid substitution table: In addition to the alignment, the construction of a profile also needs an amino acid substitution table. We have found that in some cases a new table, the BLOSUM45 table (Henikoff S, Henikoff JG, 1992, Proc Natl Acad Sci USA 89:10915-10919), is more sensitive than the original Dayhoff table or the modified Dayhoff table used in the current implementation. Profiles derived by the improved method are more sensitive and selective in a number of cases where previous methods have failed to completely separate true members from false positives.

Exact and approximate stepdown methods for multiple hypothesis testing

Consider the problem of testing k hypotheses simultaneously. In this paper,we discuss finite and large sample theory of stepdown methods that providecontrol of the familywise error rate (FWE). In order to improve upon theBonferroni method or Holm's (1979) stepdown method, Westfall and Young(1993) make eective use of resampling to construct stepdown methods thatimplicitly estimate the dependence structure of the test statistics. However,their methods depend on an assumption called subset pivotality. The goalof this paper is to construct general stepdown methods that do not requiresuch an assumption. In order to accomplish this, we take a close look atwhat makes stepdown procedures work, and a key component is a monotonicityrequirement of critical values. By imposing such monotonicity on estimatedcritical values (which is not an assumption on the model but an assumptionon the method), it is demonstrated that the problem of constructing a validmultiple test procedure which controls the FWE can be reduced to the problemof contructing a single test which controls the usual probability of a Type 1error. This reduction allows us to draw upon an enormous resamplingliterature as a general means of test contruction.

From correspondence analysis to multiple and joint correspondence analysis

The generalization of simple (two-variable) correspondence analysis to more than two categorical variables, commonly referred to as multiple correspondence analysis, is neither obvious nor well-defined. We present two alternative ways of generalizing correspondence analysis, one based on the quantification of the variables and intercorrelation relationships, and the other based on the geometric ideas of simple correspondence analysis. We propose a version of multiple correspondence analysis, with adjusted principal inertias, as the method of choice for the geometric definition, since it contains simple correspondence analysis as an exact special case, which is not the situation of the standard generalizations. We also clarify the issue of supplementary point representation and the properties of joint correspondence analysis, a method that visualizes all two-way relationships between the variables. The methodology is illustrated using data on attitudes to science from the International Social Survey Program on Environment in 1993.

Multiple filtering devices for the estimation of cyclical DSGE models

We propose a method to estimate time invariant cyclical DSGE models using the informationprovided by a variety of filters. We treat data filtered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and non-structuralparameters jointly using a signal extraction approach. We employ simulated data to illustratethe properties of the procedure and compare our conclusions with those obtained when just onefilter is used. We revisit the role of money in the transmission of monetary business cycles.

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.

Effect of multiple oral doses of androgenic anabolic steroids on endurance performance and serum indices of physical stress in healthy male subjects.

Anabolic androgenic steroids (AAS) are doping agents that are mostly used for improvement of strength and muscle hypertrophy. In some sports, athletes reported that the intake of AAS is associated with a better recovery, a higher training load capacity and therefore an increase in physical and mental performances. The purpose of this study was to evaluate, the effect of multiple doses of AAS on different physiological parameters that could indirectly relate the physical state of athletes during a hard endurance training program. In a double blind settings, three groups (n = 9, 8 and 8) were orally administered placebo, testosterone undecanoate or 19-norandrostenedione, 12 times during 1 month. Serum biomarkers (creatine kinase, ASAT and urea), serum hormone profiles (testosterone, cortisol and LH) and urinary catecholamines (noradrenalin, adrenalin and dopamine) were evaluated during the treatment. Running performance was assessed before and after the intervention phase by means of a standardized treadmill test. None of the measured biochemical variables showed significant impact of AAS on physical stress level. Data from exercise testing on submaximal and maximal level did not reveal any performance differences between the three groups or their response to the treatment. In the present study, no effect of multiple oral doses of AAS on endurance performance or bioserum recovery markers was found.

Measurement of Bioactivity of Immunomodulatory Treatment of Relapsing Multiple Sclerosis. With Emphasis on MxA Protein

Background Multiple sclerosis (MS) is a demyelinating disease of the central nervous system, which mainly affects young adults. In Finland, approximately 2500 out of 6000 MS patients have relapsing MS and are treated with disease modifying drugs (DMD): interferon- β (INF-β-1a or INF-β-1b) and glatiramer acetate (GA). Depending on the used IFN-β preparation, 2 % to 40 % of patients develop neutralizing antibodies (NAbs), which abolish the biological effects of IFN-β, leading to reduced clinical and MRI detected efficacy. According to the Finnish Current Care Guidelines and European Federation of Neurological Societis (EFNS) guidelines, it is suggested tomeasure the presence of NAbs during the first 24 months of IFN-β therapy. Aims The aim of this thesis was to measure the bioactivity of IFN-β therapy by focusing on the induction of MxA protein (myxovirus resistance protein A) and its correlation to neutralizing antibodies (NAb). A new MxA EIA assay was set up to offer an easier and rapid method for MxA protein detection in clinical practice. In addition, the tolerability and safety of GA were evaluated in patients who haddiscontinued IFN-β therapy due to side effects and lack of efficacy. Results NAbs developed towards the end of 12 months of treatment, and binding antibodies were detectable before or parallel with them. The titer of NAb correlated negatively with the amount of MxA protein and the mean values of preinjection MxA levels never returned to true baseline in NAb negative patients, but tended to drop in the NAb positive group. The test results between MxA EIA and flow cytometric analysis showed significant correlation. GA reduced the relapse rate and was a safe and well-tolerated therapy in IFN-β-intolerant MS patients. Conclusions NAbs inhibit the induction of MxA protein, which can be used as a surrogate marker of the bioactivity of IFN-β therapy. Compared to flow cytometricanalysis and NAb assay, MxA-EIA seemed to be a sensitive and more practical method in clinical use to measure the actual bioactivity of IFN-β treatment, which is of value also from a cost-effective perspective.

Simultaneous identification of multiple mammalian species from mixed forensic samples based on mtDNA control region length polymorphism

Molecular species identification in mixed or contaminated biological material has always been problematic. We developed a simple and accurate method for mammal DNA identification in mixtures, based on interspecific mitochondrial DNA control region length polymorphism. Contrary to other published methods dealing with species mixtures, our protocol requires a single universal primer pair and amplification step, and is not based on a pre-defined panel of species. This protocol has been routinely employed by our laboratory for species identification in dozens of human and animal forensic caseworks. Six representative forensic caseworks involving the specific identification of mixed animal samples are reported in this paper, in order to demonstrate the applicability and usefulness of the method.

Simultaneous Optical Recording in Multiple Cells by Digital Holographic Microscopy of Chloride Current Associated to Activation of the Ligand-Gated Chloride Channel GABA(A) Receptor.

Chloride channels represent a group of targets for major clinical indications. However, molecular screening for chloride channel modulators has proven to be difficult and time-consuming as approaches essentially rely on the use of fluorescent dyes or invasive patch-clamp techniques which do not lend themselves to the screening of large sets of compounds. To address this problem, we have developed a non-invasive optical method, based on digital holographic microcopy (DHM), allowing monitoring of ion channel activity without using any electrode or fluorescent dye. To illustrate this approach, GABA(A) mediated chloride currents have been monitored with DHM. Practically, we show that DHM can non-invasively provide the quantitative determination of transmembrane chloride fluxes mediated by the activation of chloride channels associated with GABA(A) receptors. Indeed through an original algorithm, chloride currents elicited by application of appropriate agonists of the GABA(A) receptor can be derived from the quantitative phase signal recorded with DHM. Finally, chloride currents can be determined and pharmacologically characterized non-invasively simultaneously on a large cellular sampling by DHM.

New multiple matched filter: design and experimental realization

A method of making a multiple matched filter which allows the recognition of different characters in successive planes in simple conditions is proposed. The generation of the filter is based on recording on the same plate the Fourier transforms of the different patterns to be recognized, each of which is affected by different spherical phase factors because the patterns have been placed at different distances from the lens. This is proved by means of experiments with a triple filter which allows satisfactory recognition of three characters.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

Genetic association tests: a method for the joint analysis of family and case-control data.

With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.

Method to estimate soil macroporosity and microporosity based on sand content and bulk density

Macroporosity is often used in the determination of soil compaction. Reduced macroporosity can lead to poor drainage, low root aeration and soil degradation. The aim of this study was to develop and test different models to estimate macro and microporosity efficiently, using multiple regression. Ten soils were selected within a large range of textures: sand (Sa) 0.07-0.84; silt 0.03-0.24; clay 0.13-0.78 kg kg-1 and subjected to three compaction levels (three bulk densities, BD). Two models with similar accuracy were selected, with a mean error of about 0.02 m³ m-3 (2 %). The model y = a + b.BD + c.Sa, named model 2, was selected for its simplicity to estimate Macro (Ma), Micro (Mi) or total porosity (TP): Ma = 0.693 - 0.465 BD + 0.212 Sa; Mi = 0.337 + 0.120 BD - 0.294 Sa; TP = 1.030 - 0.345 BD 0.082 Sa; porosity values were expressed in m³ m-3; BD in kg dm-3; and Sa in kg kg-1. The model was tested with 76 datum set of several other authors. An error of about 0.04 m³ m-3 (4 %) was observed. Simulations of variations in BD as a function of Sa are presented for Ma = 0 and Ma = 0.10 (10 %). The macroporosity equation was remodeled to obtain other compaction indexes: a) to simulate maximum bulk density (MBD) as a function of Sa (Equation 11), in agreement with literature data; b) to simulate relative bulk density (RBD) as a function of BD and Sa (Equation 13); c) another model to simulate RBD as a function of Ma and Sa (Equation 16), confirming the independence of this variable in relation to Sa for a fixed value of macroporosity and, also, proving the hypothesis of Hakansson & Lipiec that RBD = 0.87 corresponds approximately to 10 % macroporosity (Ma = 0.10 m³ m-3).