bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decompositions for 2‐Ratios‐Parameter Symmetry Model in Square Contingency Tables with Ordered Categoriesat
Authors: Tomizawa Sadao 
Published: May 2007

AbstractFor square contingency tables with ordered categories, Agresti (1983) considered the linear diagonals‐parameter symmetry model. An extended model including that model is proposed which has only one more parameter than that model. The model also includes the conditional symmetry model considered by McCullagh (1978). Decompositions for the proposed model and Agresti's model are given.
A Simple Survival Model for Combined Action of Two Damaging Agents
Authors: Tanushev M. , Myasnikova E. M. , Yakovlev A. Yu. 
Published: May 2007

AbstractThe aim of this study was mathematical formalization of the development of two damage processes in response to the combined action of two different damaging agents. The model allows to obtain the parametric family of distributions for the life‐span when the organism's death is due to joint effect of two damage processes. Differing by their probabilistic meaning the notions of a priori (M(t)) and a posteriori (M(y)) conditional mean contributions of each damage process to the final effect of combined injury are introduced. The formulas permitting to compute theMandMvalues on the basis of survival data parametric analysis are given.
Associated LAH Numbers, Factorial Series Distributions and Unbiased Estimation of a Size Parameter
Authors: Berg S. 
Published: May 2007

AbstractA finite population consists of kN individuals of N different categories with k individuals each. It is required to estimate the unknown parameter N, the number of different classes in the population. A sequential sampling scheme is considered in which individuals are sampled until a preassigned number of repetitions of already observed categories occur in the sample. Corresponding fixed sample size schemes were considered by Charalambides (1981). The sequential sampling scheme has the advantage of always allowing unbiased estimation of the size parameter N. It is shown that relative to Charalambides' fixed sample size scheme only minor adjustments are required to account for the sequential scheme. In particular, MVU estimators of parametric functions are expressible in terms of the C‐numbers introduced by Charalambides.
Information in Observation Under the Correlated Linear Model
Authors: Ghosh Subir 
Published: May 2007

AbstractIn this paper we propose a measure of information in a set of observations under a given design and the linear model with the observations being correlated. We then compare the different sets of observations with respect to the information measure in the situations where the underlying designs are nested and split‐plot.AMS 1970 Subject Classification: Secondary 62J05, 62J10, 62K05, 62K10, 62K15, 62K99.
Relating Cox's Proportional Hazard Model to the Exponential Model for Survival
Authors: Maller R. A. 
Published: May 2007

AbstractAn approximate representation is given for the partial likelihood estimate of the regression coefficient in Cox's proportional hazard model which indicates how it measures the association between survival time and covariate. The case of a single covariate is concentrated on. The representation is closely related to the first step of a Newton‐Raphson iteration, i.e. to the score test. A similar representation for the Feigl‐Zelen exponential model shows that a similar type of association is being measured, if observed lifetimes are interpreted as expected lifetimes of ordered exponentials. Necessary and sufficient conditions for the existence of Cox's estimate in the simple case are also written down.
Estimation and Tests for Departures from Rao‐Structured Covariance Matrices
Authors: Ghosh Subir , Gokhale D. V. 
Published: May 2007

AbstractFor linear models, a measure of departure of a variance‐covariance matrix from Rao‐structure (Rao, 1967) is proposed. Relevant estimation and testing problems are discussed. Illustrative examples are also presented.
Assessing the Effect of the Best Treatment. A Non‐parametric Inference Problem
Authors: Lanke Jan 
Published: May 2007

AbstractFor patients of a certain type, a number of treatments are available. The effect of each such treatment is assumed to be described by a shift model; it is, however, admitted that there may be an interaction between patient and treatment, meaning in particular that the treatment which is best for one patient is not necessarily best for another. The problem is the following: if each patient is given the treatment which is optimal for that particular patient, will this produce a significant effect and, if so, how large is the effect?
Estimation of Error Rates by Means of Simulated Bootstrap Distributions
Authors: Wernecke K.‐D. , Kalb G. 
Published: May 2007

AbstractThe bootstrap error estimation method is investigated in comparison with the known π‐method and with a combined error estimation suggested by us using simulated and normally distributed “populations” in 15 and 30 characters, respectively. For small sample sizes (below the double to threefold number of characters per class) the estimates resulting from the bootstrap method are on the average too small and can no longer be accepted. Significantly better results (with an essentially lower calculation expenditure) are obtained for the π‐method and the combined estimation. The variability is essentially the same for all the three methods.This applies both in the case of rather badly separated and in the case of very well separated populations.A bootstrap estimation modified by us also gives unsatisfactory results.
A Growth Curve Analysis for Bulls Tested at Station
Authors: Liski E. P. 
Published: May 2007

AbstractData on 2712 bulls tested at station were analysed to study the effect of certain external variables on growth traits of bulls. Most of the animals were Ayrshires (2136). Otherwise Finncattle bulls and Frisian bulls were involved. The testing covers the interval 60–365 days of age, although in part of the data the period is 30–365. Bulls were weighted every 30th day (between 1965 and 1970), or at the ages of 60 and 180 days, and thereafter every 30 days up to the age of 365 days (between 1971 and 1977). Also birth weight was available for 1250 calves. Feeding and general treatment of bulls at station was as uniform as possible for all animals. Conseqúently it can be assumed that effects of non‐genetic factors on the growth traits of bulls are minimized.One of the objectives of this study was to compare the growth curves for the three breeds. In our data measurements at certain time‐points have dropped out during the course of data collection.Therefore we study the influence of deleting measurements. We also consider the problem of influential measurements at both the design level and the inference level. Several types of growth curves are fitted to the data in order to find the most appropriate model.
On Some Problems in Measuring Change on Ordinal Data
Authors: Krause B. , Raykov T. 
Published: May 2007

AbstractTwo designs frequently occurring in biomedicine and social sciences are considered—the “experts”/“objects”—design consisting in ranking M fixed “objects” by each of N “experts” before and after an intervention, and the rating‐scale‐design in which N judges are asked to assign one of K given lables, constituting the rating‐scale, before and after an intervention. Nonparametric test procedures are proposed for evaluating the treatment effect.
The Analysis of Partial Diallel Crosses
Authors: Ceranka B. , Dobek A. , Kiełozewska H. 
Published: May 2007

AbstractThe analysis of offsprings from the partial diallel crosses is presented. In considered type of crossing,pparental forms intoHseparate groups are devided. Single crosses among parental forms, from separate groups only, are performed. The analysis for experiments laid out in efficiency balanced block designs is given.
Probability of Obtaning Negative Estimates of Heritability from Full‐Sib Analysis under a General Model of Gene Action
Authors: Prabhakaran V. T. , Jain J. P. 
Published: May 2007

AbstractFormulae are derived for the probability of obtaining negative estimates of heritability (h2) in full‐sib analysis under the additive‐dominance‐epistasis model of gene action. Evaluation of the probabilities was undertaken for several combinations of sire/dam number, h2 and proportions of dominance and additive X additive epistatic variances, assuming two full‐sibs per mating and that the dominance related epistasis is absent. In the light of the results, minimum sample sizes for obtaining admissible estimates from sire, dam components and their combination have been prescribed.
Bayes Estimator of Survival Probability from Randomly Censored Observations with Weibull Distribution of Time to Death
Authors: Pandey M. 
Published: May 2007

AbstractThis paper deals with Bayes estimation of survival probability when the data are randomly censored. Such a situation arises in case of a clinical trial which extends for a limited period T. A fixed number of patients (n) are observed whose times to death have identical Weibull distribution with parameters β and θ. The maximum times of observation for different patients are also independent uniform variables as the patients arrive randomly throughout the trial. For the joint prior distribution of (β, θ) as suggested by Sinha and Kale (1980, page 137) Bayes estimator of survival probability at time t (0<t<T) has been obtained. Considering squared error loss function it is the mean of the survival probability with respect to the posterior distribution of (β, θ). This estimator is then compared with the maximum likelihood estimator, by simulation, for various values of β, θ and censoring percentage. The proposed estimator is found to be better under certain conditions.
Rank Tests for the 2×2 Design with I Blocks
Authors: Haux R. , Mattauch V. , Weckesser G. 
Published: May 2007

AbstractIn this paper we suggest rank tests for main effects and for interaction when there are two factors and two levels within each factor and when, in addition, there are I blocks. The asymptotic distributions of the test statistics under H0 are derived. The application of the tests is illustrated by an example and a simulation study investigates size and power of the tests.
Approximate Methodologies for Proportional Mortality Analyses in Epidemiologic Studies Involving Competing Risks of Death Regardless of their Covariance Structure
Authors: Rao B. Raja , Marsh Gary M. 
Published: May 2007

AbstractThe present paper discusses methodologies for proportional mortality analyses in epidemiologic studies in which an individual is exposed simultaneously to several (say M) risks of death which compete for his life. A general situation is considered where nothing is known about the dependence or covariance structure among the risks. The available data consist only of the number of deaths in each stratum of the test population, but not the number of individuals at risk. A general class of approximate simultaneous confidence and prediction intervals are developed which provide overall risk assessment of the competing risk factors in many biomedical and epidemiologic studies. Our paper describes how, under reasonable assumptions, asymptotically precise inferences may be based on proportional mortality analyses in order to estimate the indirectly and the externally standardized cause‐specific risk measures RSMRi and RSRRi respectively.The tuberculosis mortality data of Kupper, et al., (1978) and the respiratory cancer mortality data of Enterline and Marsh (1983) are utilized to illustrate the usefulness of our results. Methodologies are presented to construct simultaneous confidence intervals for RSMRi involving SPMRi and simultaneous prediction intervals for RSRRi involving SePMRi. Both Scheffé‐and Sidak‐Types of simultaneous intervals are constructed for M competing risks of death. As a particular case if M = 1, i.e., if the risks of death may be assumed to be independent, as is usually done in proportional mortality analyses, the Scheffé and Sidak confidence intervals become identical and are narrower than of Kupper et al., (1978). In this sense, our paper generalizes the methodologies of proportional mortality analyses in two directions, first to discuss the situation involving competing risks, and second to obtain narrower confidence intervals.
Utilizing Cause‐of‐Death Information to Estimate Conditional Probabilities of Disease and Death
Authors: Kodell Ralph L. 
Published: May 2007

AbstractConditional probabilities that do not require the assumption of independence among competing risks for identifiability are proposed for the analysis of carcinogenesis bioassay data as a reasonable adjustment for deaths or other removals due to competing risks. These conditional probabilities permit consideration of one type of tumor at a time, but in such a way that inferences are relevant to actual experimental conditions under which other diseases and causes of death are present and operating. The importance of assigning cause of death in bioassays is demonstrated by the fact that it allows the definition and identification of functions useful in the interpretation of carcinogenesis data, without requiring that a disease of interest be independent from competing risks. However, one proposed conditional probability does require sacrifice data for its identifiability.
Using a Generalized Mean as a Measure of Location
Authors: Taylor Jeremy M. G. 
Published: May 2007

AbstractIn Taylor (1985 a) a measure of location, akin to a generalised mean was proposed, it's properties were studied for a particular family of skew distributions. The measure of location is essentially the retransformed mean after first transforming the observations to an approximately symmetric scale. Here it's properties are investigated for more general skew distributions. In particular, we study whether it satisfies the axioms for measures of location given in Bickel and Lehmann (1975). We show that it is estimating approximately the distribution median and through simulations we show that it is more efficient than the sample median.
Analysis of Colony‐Forming Ability of Human Fibroblast Strains by Linear Regression
Authors: Edler Lutz , Thielmann Heinz Walter 
Published: May 2007

AbstractA linear regression approach is presented for the statistical analysis of dose‐response curves obtained by measuring the colony‐forming ability of human fibroblast strains. The crucial determination of the dose range in which the linear model can be assumed is achieved by a combination of statistical criteria and biological claims. As a basic quantitative parameter we investigate the slope of the regression line and, by taking reciprocals, we retransform it into the biologically established parameter D0. Several methods for the combination of estimates are presented.
Normal Approximations of Exact Tests in Configural Frequency Analysis
Authors: Bergman L. R. , von Eye A. 
Published: May 2007

AbstractThe most common tests for types and antitypes in configural frequency analysis are normal approximations of exact tests. In the paper such statistics under the complete independence model and under the fixed margins model are discussed. It turns out that these test statistics are not acceptable when the number of simultaneously performed tests is large or when the expected frequencies are small. In these cases, the use of exact tests is advocated and some existing computer programs for such tests are indicated. A normal approximation based on the strong version of the De Moivre‐Laplace limit theorem is also discussed. Empirical examples are given from longitudinal data describing psychological development of boys.
The Hyper‐Negative Binomial Distribution
Authors: Yousry M. A. , Srivastava R. C. 
Published: May 2007

AbstractA generalized family of the negative binomial distribution is introduced in a paper by Srivastava, Yousry and Ahmed (1986). It is a solution of the difference equation
equation image
and is called the hyper‐negative binomial distribution. Certain properties including the moments of the distribution are presented. Moment estimators of the parameters are obtained and goodness of fit is illustrated for chromatid aberration data.
Estimation of Growth Norms from Incomplete Longitudinal Data
Authors: Woolson Robert F. , Clarke William R. 
Published: May 2007

AbstractLongitudinal studies are rarely complete due to attrition, mistimed visits and observations missing at random. When the data are missing at random it is possible to estimate the primary location parameters of interest by constructing a modification of Zellner's (1962) seemingly unrelated regression estimator. Such a procedure is developed in this paper and is applied to a longitudinal study of coronary risk factors in children. The method consists of two stages in which the covariance matrix is estimated at the first stage. Using the estimated covariance matrix a generalized least squares estimator of the regression parameter vector is then determined at the second stage. Limitations of the procedure are also discussed.
Randomization and Additivity in the Two‐Period Crossover Clinicial Trial
Authors: McHugh Richard , Gomez‐Marin Orlando 
Published: May 2007

AbstractIn certain areas of medical research, the two‐period crossover design is a frequent choice for comparing treatments A and B in a randomized clinical trial. Earlier work by Grizzle and by Brown was based upon a parametric theory linear model. Recently, the present authors employed D. R. Cox's additive randomization models and, for the case of zero residual effect, found a discrepancy between it and the parametric model with respect to the precision of period effects. In the present note, this divergence is accounted for by allowing for the possibility of non‐additivity through the use of a completely general randomization model. It is concluded that the structure of the crossover design is such that use of the parametric theory linear model is required if a single, consistent model is desired.
Analysis of Multiply Matched Retrospective Studies When Risk Factor Under Study is Discrete, With Two or More Levels
Authors: Ejigou Ayenew 
Published: May 2007

AbstractThe odds ratio is known to closely approximate the relative risk when the disease is rare. Logistic regression models are often used to estimate such odds ratios, but here a different model is used which avoids the assumptions implicit in logistic modelling; it also has the advantage of providing a test of homogeneity for odds rat os in situations where the logistic model cannot.
Estimation of Relative Risk Under M to R Matching
Authors: Ejigou Ayenew 
Published: May 2007

AbstractEstimation of the relative risk from a rare disease is carried out using M:R matching. Both conditional and unconditional likelihood methods are used, leading in each case to the same estimate; a non‐iterative estimate is always available under M:R matching, M ≦2. The method also enables the testing of homogeneity even when information on the matching variate is unavailable and this is an advantage over logistic regression methods.
An Example of Simultaneous Multivariate Linear Modelling of Among and Within Subject Variation
Authors: Singer J. M. , Koch G. G. , Stinnett S. S. , Warren D. W. 
Published: May 2007

AbstractAn example of simultaneous linear modelling of among and within subject variation through weighted least squares methods is presented as an alternative to standard multivariate analysis of variance techniques. The data pertain to a study of temporal characteristics of some aerodynamic parameters from a speech test used to differentiate groups of individuals with different degrees of palatopharyngeal closure. Both methods are found to yield similar results with respect to the among group comparisons, but the simultaneous strategy enables some further reduction in dimensionality, and thereby extends the description of patterns in the data.
Robust continuous collision detection for interactive deformable surfaces
Authors: Wong Wingo Sai‐Keung , Baciu George 
Published: May 2007

AbstractCollision events between 3D objects in motion in computer animations or simulations are difficult to detect due to the difficulty of accurately sampling the motion paths of objects in space and time. One approach to this problem has been continuous collision detection but because the current approaches process potentially interacting primitive pairs (PIPPs) redundantly. This is time‐expensive, especially where there are a large number of PIPPs. In this paper we propose a novel collision detection process that more accurately and robustly detects collisions on simulated meshed deformable surfaces. We embed a new layer, primitive filtering layer (PFL), to extract PIPPs. This has two results. It reduces the number of PIPPs significantly and it means that each interacting primitive pair is processed just one time. Experimental results show that this approach achieves interactive rates for complex deformable surfaces with large contact regions. This is especially practical for cloth dynamics. Our method is efficient, accurate, reliable, and robust even in the presence of objects with sharp features. We also present techniques to implement the method on programmable graphics processing units (GPUs). Copyright © 2007 John Wiley & Sons, Ltd.
Age disparity between a cancer population and participants in clinical trials submitted as a new drug application of anticancer drugs in Japan
Authors: Hori Akiko , Shibata Taro , Kami Masahiro , Kusumi Eiji , Narimatsu Hiroto , Kishi Yukiko , Murashige Naoko , Mori Kazuhiko 
Published: May 2007

AbstractBACKGROUND.Underrepresentation of older patients in cancer clinical trials has been reported previously.METHODS.To evaluate disparities in age between actual cancer patients and those enrolled in clinical trials, the authors examined all the review reports of the Pharmaceuticals and Medical Devices Agency, Tokyo, Japan, and summaries of data submitted by applicants for the approval of new cancer drugs and that of a partial change in approved cancer drugs.RESULTS.Information regarding 68 clinical trials was available on the Internet. The median age of trial participants ranged from 33 years to 73 years and was older than 65 years in 13 trials, whereas the estimated median age of patients with all cancers was 69 years, and 64% of these individuals were age ≥65 years. The median age of trial participants was found to be lower than that of the patient population in 60 trials. The median difference in age between the 2 groups was 7 years (range, −16 to +33). With regard to molecular‐targeting agents (16 trials) and hormonal agents (10 trials), trial participants were younger than the patient population in 25 of the 26 trials, with a median difference of 6 years (range, −9.5 to +20). The difference was larger for molecular‐targeting agents (median, 9.5 years; range, birth‐20 years) compared with hormonal agents (median, 2 years; range, −9.5 to +15).CONCLUSIONS.The results of the current study show that participants in cancer clinical trials are younger than the actual Japanese cancer patient population. Cancer 2007. © 2007 American Cancer Society.
Fast transimpedance switching burst‐mode CMOS optical receiver
Authors: Schneider Kerstin , Zimmermann Horst 
Published: May 2007

AbstractThis work shows that the performance of optical receivers designed in silicon deep‐sub‐micron CMOS technologies competes successfully with more expensive SiGe‐BiCMOS receivers in data rate and sensitivity. In burst‐mode applications of passive optical networks, the transimpedance of the low‐noise amplifier has to be switched very fast requiring, the exclusion of oscillations. To meet the burst‐mode requirements, our design for 2.5 G bit/s in 120 nm CMOS offers a fast switching of the transimpedance within 3 ns and proves a low‐distortion signal detection. Copyright © 2007 John Wiley & Sons, Ltd.