bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wärmedämmstoffe in Deutschland nach europäischen Normen: Nicht nur ein Problem für Sachverständige
Authors: Cziesielski Erich 
Published: October 2004

AbstractDie harmonisierten europäischen Produktnormen für werkmäßig hergestellte Wärmedämmstoffe EN 13162 bis EN 13171 sind auf der Grundlage der vom europäischen Rat 1989 erlassenen Bauproduktenrichtlinie erarbeitet worden. Das Deutsche Institut für Normung (DIN) hat diese Normen im Oktober 2001 veröffentlicht. Nach der Koexistenzperiode, während der in Deutschland die Dämmstoffe sowohl mit dem CE‐ als auch mit dem Ü‐Zeichen in den Verkehr gebracht werden konnten, gilt seit dem 15.05.2003, daß nationale Normen, die den hamonisierten Normen entgegenstehen, zurückgezogen werden müssen. Die nationalen Normen, die den harmonisierten Normen nicht entgegenstehen, bleiben aber einschließlich der dazugehörigen Prüfnormen weiterhin gültig.Der folgende Beitrag soll dazu dienen, den am Bau Tätigen die neuen harmonisierten Produktnormen bezüglich der Wärmedämmstoffe und vor allem die neue Methodik und Symbolik von Produkteigenschaften zu erläutern. Weiterhin soll die von der Dämmstoffindustrie zum Teil vorgenommene Qualitätssicherung durch CE‐ und Ü‐Zeichen begründet werden.
Modelling Heterogeneous Dispersion in Marginal Models for Longitudinal Proportional Data
Authors: Song Peter X.‐K. , Qiu Zhenguo , Tan Ming 
Published: October 2004

AbstractContinuous proportional data is common in biomedical research, e.g., the pre‐post therapy percent change in certain physiological and molecular variables such as glomerular filtration rate, certain gene expression level, or telomere length. As shown in (Song and Tan, 2000) such data requires methods beyond the common generalised linear models. However, the original marginal simplex model of (Song and Tan, 2000) for such longitudinal continuous proportional data assumes a constant dispersion parameter. This assumption of dispersion homogeneity is imposed mainly for mathematical convenience and may be violated in some situations. For example, the dispersion may vary in terms of drug treatment cohorts or follow‐up times. This paper extends their original model so that the heterogeneity of the dispersion parameter can be assessed and accounted for in order to conduct a proper statistical inference for the model parameters. A simulation study is given to demonstrate that statistical inference can be seriously affected by mistakenly assuming a varying dispersion parameter to be constant in the application of the available GEEs method. In addition, residual analysis is developed for checking various assumptions made in the modelling process, e.g., assumptions on error distribution. The methods are illustrated with the same eye surgery data in (Song and Tan, 2000) for ease of comparison. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Nonparametric Modeling of the Mean Survival Time in a Multi‐factor Design Based on Randomly Right‐Censored Data
Authors: Rahbar M. H. , Gardiner J. C. 
Published: October 2004

AbstractStatistical procedures and methodology for assessment of interventions or treatments based on medical data often involves complexities due to incompleteness of the available data as a result of drop out or the inability of complete follow up until the endpoint of interest. In this article we propose a nonparametric regression model based on censored data when we are concerned with investigation of the simultaneous effects of the two or more factors. Specifically, we will assess the effect of a treatment (dose) and a covariate (e.g., age categories) on the mean survival time of subjects assigned to combinations of the levels of these factors. The proposed method allows for varying levels of censorship in the outcome among different groups of subjects at different levels of the independent variables (factors). We derive the asymptotic distribution of the estimators of the parameters in our model, which then allows for statistical inference. Finally, through a simulation study we assess the effect of the censoring rates on the standard error of these types of estimators. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Use of Covariates and Survey Wave to Adjust for Nonresponse
Authors: Rao R. Sowmya , Glickman Mark E. , Glynn Robert J. 
Published: October 2004

AbstractUsing covariates available on all sampled individuals along with an intensive follow‐up of nonrespondents is a useful approach to reduce the impact of nonresponse. We examined the performance of several different nonresponse models to account for such covariates and multiple survey waves to estimate the prevalence of birth control use in 106463 women taking the teratogenic drug Accutane. Nonrespondents to a first mailing were followed with two more mailings and then a telephone call. The first mailing had a response rate of 59.7 percent; the overall nonresponse rate was 15.2 percent. Age was available on all women and was strongly associated with both response and birth control use. We considered both multiple imputation and weighting strategies using information on age and time to response assuming that nonrespondents were: (i) like all respondents conditional on age, (ii) like reluctant respondents conditional on age, and (iii) projected from a model which includes trend. Simulation studies were used to examine the potential bias in this setting and we compared models under different assumptions about the missing data mechanism. Results describe the extent to which availability of covariate information and use of multiple waves improves estimation. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
K‐Sample Test and Sample Size Calculation for Comparing Slopes in Data with Repeated Measurements
Authors: Jung Sin‐Ho , Ahn Chul 
Published: October 2004

AbstractSample size calculations based on two‐sample comparisons of slopes in repeated measurements have been reported by many investigators. In contrast, the literature has paid relatively little attention to the design and analysis of K‐sample trials in repeated measurements studies where K is 3 or greater. Jung and Ahn (2003) derived a closed sample size formula for two‐sample comparisons of slopes by taking into account the impact of missing data. We extend their method to compare K‐sample slopes in repeated measurement studies using the generalized estimating equation (GEE) approach based on independent working correlation structure. We investigate the performance of the sample size formula since the sample size formula is based on asymptotic theory. The proposed sample size formula is illustrated using a clinical trial example. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Centre‐effect on Survival after Bone Marrow Transplantation: Application of Time‐dependent Frailty Models
Authors: Wintrebert Claire M. A. , Putter Hein , Zwinderman Aeilko H. , van Houwelingen J.C. 
Published: October 2004

AbstractIn many biomedical investigations, multivariate or clustered failure time data are encountered. They arise for instance, when the sample consists of centres and each centre contains several patients. For this kind of data, frailty models can be used to take into account the possible correlation within centres. Most common are centre‐specific frailty models in which the centre‐effect on failure time is assumed to be constant with follow‐up. But with many applications this assumption is too restrictive. More realistic are models with time‐varying frailties. Therefore, we studied ways to extend the constant centre‐specific frailty model to allow time dependence of the frailties. To begin, we followed and adapted Paik et al. (1994) who generalized the shared frailty model by introducing additional random frailty terms for different time‐intervals. Although, the model allows the frailty to vary between intervals, it is very cumbersome to calculate and difficult to fit. We developed two much simpler centre‐specific frailty models. First, we proposed a model with a power parameter in which the “effect” of the centre‐specific frailty is allowed to vary between intervals. And secondly, we extended the model permitting the centre‐specific frailty to vary with time. Although the convenience of the gamma and positive stable frailty models is lost in both extensions of the frailty model, the computations of these models are much easier than of the adapted Paik's model. We applied these time‐dependent frailty models to a data set from the European Blood Marrow Transplant (EBMT) registry, where a decaying centre‐effect was found. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
A New Testing Approach for Comparing the Overall Homogeneity of Survival Curves
Authors: Lin Xun , Wang Hongkun 
Published: October 2004

AbstractThe assessment of overall homogeneity of time‐to‐event curves is a key element in survival analysis. The currently commonly used methods, e.g., log‐rank and Wilcoxon tests, may have a significant loss of statistical testing power under certain circumstances. In this paper a new statistical testing approach is developed to compare the overall homogeneity of survival curves. The proposed new method has greater power than the commonly used tests to detect overall differences between crossing survival curves. The small‐sample performance of the new test is investigated under a variety of situations by means of Monte Carlo simulations. Furthermore, the applicability of the proposed testing approach is illustrated by a real data example from a kidney dialysis trial. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
An Independence Test for Doubly Censored Failure Time Data
Authors: Sun Jianguo , Lim Hee‐Jeong , Zhao Xingqiu 
Published: October 2004

AbstractThe analysis of doubly censored failure time data has recently attracted a great deal of attention and for this, a number of methods have been proposed (De Gruttola and Lagakos, 1989; Kim et al., 1993; Pan, 2001; Sun, 2004). To simplify the analysis, most of these methods make an independence assumption: the distribution of the survival time of interest is independent of the occurrence of the initial event that defines the survival time. Although it is well‐known that the assumption may not be true, there does not seem to be any existing research discussing the checking of the assumption. In this article, a Wald test is developed for testing this assumption and the method is applied to an AIDS cohort study. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Testing for Poisson Zero Inflation in Disease Mapping
Authors: Ugarte M. Dolores , Ibáńez B. , Militino A. F. 
Published: October 2004

AbstractWhen analyzing mortality data due to rare diseases in small areas, it is common to find several health zones with no mortality cases. In these circumstances, the classical homogeneous model based on the Poisson distribution used to estimate the relative risks within each area may encounter lack of fit due to a disproportionately large frequency of zeros. To cope with these zeros, the zero inflated Poisson model can be used. In this paper, we propose a test for detecting zero inflation in the context of disease mapping which is based on bootstrap techniques. The test is illustrated using male mortality data due to brain cancer in Navarra, Spain. In addition, comparisons with other tests for Poisson zero inflation such as the score test and the likelihood ratio test are carried out in terms of empirical power and size using the brain cancer scenario. The proposed bootstrap test has good power and size and works well when detecting the excess of zeros in small area data sets. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Analytical Relationship between Family History and Genetic and Environmental risks, with Application to Female Breast Cancer
Authors: Cui Jisheng S. 
Published: October 2004

AbstractIt is well established in genetic epidemiology that family history is an important indicator of familial aggregation of disease in a family. A strong genetic risk factor or an environmental risk factor with high familial correlation can result in a strong family history. In this paper, family history refers to the number of first‐degree relatives affected with the disease. Cui and Hopper (Journal of Epidemiology and Biostatistics 2001; 6: 331–342) proposed an analytical relationship between family history and relevant genetic parameters. In this paper we expand the relationship to both genetic and environmental risk factors. We established a closed‐form formula for family history as a function of genetic and environmental parameters which include genetic and environmental relative risks, genotype frequency, prevalence and familial correlation of the environmental risk factor. The relationship is illustrated by an example of female breast cancer in Australia. For genetic and environmental relative risks less than 10, most of the female breast cancer cases occur between the age of 40 and 60 years. A higher genetic or environmental relative risk will move the peak of the distribution to a younger age. A more common disease allele or more prevalent environmental risk factor will move the peak to an older age. For a proband with breast cancer, it is most likely (with probability ≥80%) that none of her first‐degree relatives is affected with the disease. To enable the probability of having a positive family history to reach 50%, the environmental relative risks must be extremely as high as 100, the familial correlation as high as 0.8 and the prevalence as low as 0.1. For genetic risk alone, even the relative risk is as high as 100, the probability of having a positive family history can only reach about 30%. This suggests that the environmental risk factor seems to play a more important role in determining a strong family history than the genetic risk factor. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Valid Adjustment of Randomized Comparisons for Binary Covariates
Authors: Berger Vance W. 
Published: October 2004

AbstractIn randomized trials, the treatment influences not only endpoints but also other variables measured after randomization which, when used as covariates to adjust for the observed imbalance, become pseudo‐covariates. There is a logical circularity in adjusting for a pseudo‐covariate because the variability in the endpoint that is attributed not to the treatment but rather to the pseudo‐covariate may actually represent an effect of the treatment modulated by the pseudo‐covariate. This potential bias is well known, but we offer new insight into how it can lead to reversals in the direction of the apparent treatment effect by way of stage migration. We then discuss a related problem that is not generally appreciated, specifically how the absence of allocation concealment can lead to this reversal of the direction of the apparent treatment effect even when adjustment is for a true covariate measured prior to randomization. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Sample Size Calculations for the Mean in a Two Component Nonstandard Mixture Distribution
Authors: Chu Haitao , Ren Shiquan , Cole Stephen R. 
Published: October 2004

AbstractWe are concerned with calculating the sample size required for estimating the mean of the continuous distribution in the context of a two component nonstandard mixture distribution (i.e., a mixture of an identifiable point degenerate function F at a constant with probability P and a continuous distribution G with probability 1 – P). A common ad hoc procedure of escalating the naïve sample size n (calculated under the assumption of no point degenerate function F) by a factor of 1/(1 – P), has about 0.5 probability of achieving the pre‐specified statistical power. Such an ad hoc approach may seriously underestimate the necessary sample size and jeopardize inferences in scientific investigations. We argue that sample size calculations in this context should have a pre‐specified probability of power ≥1 – β set by the researcher at a level greater than 0.5. To that end, we propose an exact method and an approximate method to calculate sample size in this context so that the pre‐specified probability of achieving a desired statistical power is determined by the researcher. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Robust Tests for Candidate‐Gene Association Using Case‐Parents Trios with a Multi‐Allelic Marker
Authors: Zheng Gang , Chen Zehua 
Published: October 2004

AbstractIn case‐parents trios design, the association between a multi‐allelic candidate‐gene and a disease can be detected by using maximum of score tests (max‐score) when the mode of inheritance is known. We apply the maximum of the max‐score statistics and the maximum of likelihood ratio statistics when the genetic model is unknown and examine their robust properties compared to max‐score statistics. The simulation results demonstrate that the two maximum robust tests are more efficacious and robust across all genetic models compared with the three max‐score tests. Moreover, in most situations, the maximum of the max‐score tests seems to be more powerful than the maximum of the likelihood ratio tests. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Using Adaptive Methods to Select Variables in Case‐Control Studies
Authors: O'Gorman Thomas W. 
Published: October 2004

AbstractA variables selection method for case‐control studies is proposed that uses an adaptive weighting scheme along with a permutation method to determine if a variable is useful in differentiating the cases from the controls. This adaptive method is used to select exposure variables for the analysis of data from a bladder cancer case‐control study. An extensive simulation study shows that the adaptive method is nearly as effective at finding those variables that are related to case‐control status when normally distributed variables are used. The simulation also shows that the proposed variable selection procedure is much more effective than the stepwise discriminant analysis method when the variables are not normally distributed. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Bayesian Predictive Probability Functions for Count Data that are Subject to Misclassification
Authors: Stamey James D. , Young Dean M. , Bratcher Tom L. 
Published: October 2004

AbstractWe develop three Bayesian predictive probability functions based on data in the form of a double sample. One Bayesian predictive probability function is for predicting the true unobservable count of interest in a future sample for a Poisson model with data subject to misclassification and two Bayesian predictive probability functions for predicting the number of misclassified counts in a current observable fallible count for an event of interest. We formulate a Gibbs sampler to calculate prediction intervals for these three unobservable random variables and apply our new predictive models to calculate prediction intervals for a real‐data example. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Aromatic interactions in peptides: Impact on structure and function
Authors: Waters Marcey L. 
Published: October 2004

AbstractAromatic interactions, including π–π, cation–π, aryl–sulfur, and carbohydrate–π interactions, have been shown to be prevalent in proteins through protein structure analysis, suggesting that they are important contributors to protein structure. However, the magnitude and significance of aromatic interactions is not defined by such studies. Investigation of aromatic interactions in the context of structured peptides has complemented studies of protein structure and has provided a wealth of information regarding the role of aromatic interactions in protein structure and function. Recent advances in this area are reviewed. © 2004 Wiley Periodicals, Inc. Biopolymers (Pept Sci), 2004
Cyclization of pyrrhocoricin retains structural elements crucial for the antimicrobial activity of the native peptide
Authors: Rosengren K. Johan , Göransson Ulf , Otvos Laszlo , Craik David J. 
Published: October 2004

AbstractPyrrhocoricin is a naturally occurring antimicrobial peptide from the European fire bug Pyrrhocoris apterus. It has submicromolar activity against a range of Gram‐negative bacterial strains and has created recent interest as a lead for the development of novel antibiotic compounds. In this study, we have used NMR spectroscopy to determine the solution structures of pyrrhocoricin and a synthetic macrocyclic derivative that has improved in vivo pharmaceutical properties. Native pyrrhocoricin is largely disordered in solution, but there is evidence of a subpopulation with ordered turn regions over residues 2–5, 4–7, and 16–19. The macrocyclic derivative incorporates a nine amino acid linker joining the N‐ and C‐termini, which does not adversely affect the antimicrobial potency but leads to a broader spectrum of activity. The NMR data suggest that the turn conformations in the cyclic derivative are similar to those in the native form, thus implicating them in the biological function. © 2004 Wiley Periodicals, Inc. Biopolymers (Pept Sci), 2004
Enantioselective Catalysis of the Hetero‐Diels–Alder Reaction between Brassard's Diene and Aldehydes by Hydrogen‐Bonding Activation: A One‐Step Synthesis of (S)‐(+)‐Dihydrokawain
Authors: Du Haifeng , Zhao Dongbo , Ding Kuiling 
Published: October 2004

AbstractThe first catalytic enantioselective hetero‐Diels–Alder reaction between Brassard's diene and aldehydes has been achieved through hydrogen‐bonding activation using TADDOL derivatives as catalysts to afford the corresponding δ‐lactone derivatives in moderate‐to‐good yields and with high enantioselectivities (up to 91 % ee). The reactions can be carried out either under solvent‐free conditions or in toluene. On the basis of the absolute configurations of the products and the hydrogen‐bonding interaction pattern between TADDOL (α,α,α′,α′‐tetraaryl‐1,3‐dioxolan‐4,5‐dimethanol) and the carbonyl group disclosed by X‐ray diffraction analysis, a possible mechanism for the catalytic reaction has been proposed. To demonstrate the usefulness of the methodology, a natural product, (S)‐(+)‐dihydrokawain, has also been prepared in 50 % isolated yield and with 69 % enantioselectivity in one step starting from 3‐phenylpropionaldehyde by using this methodology. Therefore, this catalytic system is one of the most direct approaches to the construction of δ‐lactone units, which will make the methodology very attractive for the synthesis of a variety of biologically important compounds and natural products.
Novel Hypervalent Complexes of Main‐Group Metals by Intramolecular Ligand→Metal Electron Transfer*
Authors: Driess Matthias , Dona Nicoleta , Merz Klaus 
Published: October 2004

AbstractNew fascinating electronic features of the simple diketoamine chelate ligand HN[CH2C(tBu)O]2 (1) are described. Unexpectedly, the corresponding trianionic amido‐dienolate form of 1 is capable of reducing main‐group metal atoms M after initial coordination and intramolecular L→M two‐electron transfer and of stabilizing main‐group elements in unusual low oxidation states. This is impressively shown by the synthesis and structural characterization of the novel Ge and Sn complexes 4–6 by redox reactions of lithiated 1 with the corresponding metal halides GeCl4 and MCl2 (M=Ge, Sn). Surprisingly, conversion of tris‐lithiated 1 with GeCl4 readily consumes two molar equivalents of GeCl4 and results in the formation of the neutral GeCl3 complex 4 and GeCl2. The former represents the second example of a structurally characterized neutral octahedrally coordinated germanium compound. Reaction of dilithiated 1 with GeCl2 does not lead to the expected ClGe(+2) complex but affords the novel dimeric germylene 5, whereas similar reaction using SnCl2 furnishes the monomeric stannylene (ClSn(+2) complex) 2 and elemental tin due to the higher oxidation potential of Sn(+2). Unexpectedly, a similar redox reaction of dilithiated 1 with PbCl2 furnishes the first air‐ and water‐stable lithium 1,2‐diketoimine–enolate 7 and elemental lead. Compound 7 is tetrameric in the solid state and consists of a strongly distorted Li4O4 cubic core with trigonal‐bipyramidal coordinated Li+ ions.