bluuebunny/crossref_metadata_2025_split huggingface dataset:
Confidence Limits for the Ratio of Two Binomial Proportions Based on Likelihood Scores: Non‐Iterative Method
Authors: Nam Jun‐Mo 
Published: May 2007

AbstractThe interval estimation of the ratio of two binomial proportions based on the score statistic is superior over other methods. Iterative algorithms for calculating the approximate confidence interval have been provided by, e.g., KOOPMAN (1984, Biometrics 40:513–517) and GART and NAM (1988a, Biometrics 44:323–338). This note presents the analytical solutions for upper and lower confidence limits in a closed form and gives examples for numerical illustration. The non‐iterative method is generally more desirable than the iterative method.
On Testing for Equicorrelation in Random Coefficient Models
Authors: Bhatti M. I. , Barry A. M. 
Published: May 2007

AbstractRecently BHATTI (1993) considered an efficient estimation of random coefficient model based on survey data. The main objective of this paper is to construct one sided test for testing equicorrelation coefficient in presence of random coefficients using optimal testing procedure. The test statistic is a ratio of quadratic forms in normal variables which is most powerful and point optimal invariant.
Analysis of Bacterial Spatial Patterns at the Initial Stage of Biofilm Formation
Authors: Hamilton M. A. , Johnson K. R. , Camper A. K. , Stoodley P. , Harkin G. J. , Gillis R. J. , Shope P. A. 
Published: May 2007

AbstractUsing sophisticated microscopy techniques, we observed the spatial pattern of bacteria colonizing a sterile 316L stainless steel coupon as bulk water containing bacteria flowed across the coupon. The experiments used stainless steel of differing roughness and surface chemistry. The ultimate goal was to identify surface features which influence bacterial adsorption. The immediate statistical goal was to distinguish patterns consistent with complete spatial randomness from patterns showing regularity or aggregation. This goal was accomplished by using modified analyses of distance functions commonly applied in field ecology. The method protected against a potential multiple comparisons problem. For the null value of the distance function, we calculated tolerance envelopes such that the tolerance level was simultaneous for all distances of concern. Computer simulation experiments showed that the nominal level was accurate. The methodology was effective for detecting and describing patterns of colonization known not to be completely spatially random.
A New Model of Aging: Specific Versions and Their Application
Authors: Yakovlev Andrej Yu , Tsodikov Alexandr D. , Anisimov Vladimir N. 
Published: May 2007

AbstractThis paper is concerned with some versions of a stochastic model of aging proposed recently by TYURIN et al. (1993). In contrast to the commonly used Gompertz‐Makeham approach, the model yields a bounded hazard rate, thereby providing a better description of survival of old individuals in a population. Depending on plausible biological assumptions to be tested, only a few special cases of the basic model appear to be useful in experimental data analysis. We report the results of their application to experimental data on animal longevity obtained in a follow‐up study. When interpreted in terms of the model parameters, the data suggest drastically dissimilar patterns of aging for female versus male rats.
A Bayesian Decision Procedure for Selecting Prognostic Variables Associated with Survival for Data in which Censoring is Prevalent
Authors: Fraser Martin D. , Bartolucci Alfred A. , Smith William A. , Singh Karen P. 
Published: May 2007

AbstractA Bayesian procedure is developed for the selection of concomitant variables in survival models. The variables are selected in a step‐up procedure according to the criterion of maximum expected likelihood, where the expectation is over the prior parameter space. Prior knowledge of the influence of these covariates on patient prognosis is incorporated into the analysis. The step‐up procedure is stopped when the Bayes factor in favor of omitting the variable selected in a particular step exceeds a specified value. The resulting model with the selected variables is fitted using Bayes estimates of the coefficients. This technique is applied to Hodgkin's disease data from a large Cooperative Clinical Trial Group and the results are compared to the results from the classical likelihood selection procedure.
Heterogeneous Variances in Repeated Measures
Authors: Wu Yuan , McGilchrist C. A. 
Published: May 2007

AbstractA general approach to repeated measures analysis described in MCGILCHRIST and CULLIS (1991) is extended to general linear models in which there is a homogeneous correlation structure such as a stationary process but the variances are heterogeneous over time. Models for the variance heterogeneity are suggested and results are applied to data examining the effect of enzootic pneumonia on young pigs.
A Measure to Evaluate the Closeness of Satterthwaite's Approximation
Authors: Khuri André I. 
Published: May 2007

AbstractSatterthwaite's approximation of the distribution of a nonnegative linear combination of independent mean squares is addressed in this article. A measure is developed to quantify the closeness of this approximation by using certain optimization results given by THIBAUDEAU and STYAN (1985). The main advantage of the proposed measure is to provide a theoretical framework for determining conditions under which Satterthwaite's approximation may be inadequate. This is demonstrated in three examples portraying frequently encountered problems in analysis of variance.
On the Estimation of True Treatment Response when Patients Enter Staggeredly in a Clinical Trial
Authors: Biswas S. , Chitkara Sunita 
Published: May 2007

AbstractDue to staggered entries of patients during a clinical trial, the available exposure to observe the patients under a treatment is less and non‐uniform while the patients with whom the trial is started initially are exposed to uniform exposures to the treatment. Because of this, the true response of the treatment gets masked. Here we have attempted to estimate the true response of the treatment in presence of staggered entries. Further, by Martingale approach the probability of acceptance/rejection has been worked out for both staggered and no staggered entry cases. The results are then compared with the help of a numerical example which shows that under staggered entries the treatment is rejected with higher probability.
Three Multiple Comparison Procedures for Trimmed Means
Authors: Wilcox Rand 
Published: May 2007

AbstractTwo common goals when choosing a method for performing all pairwise comparisons of J independent groups are controlling experiment wise Type I error and maximizing power. Typically groups are compared in terms of their means, but it has been known for over 30 years that the power of these methods becomes highly unsatisfactory under slight departures from normality toward heavy‐tailed distributions. An approach to this problem, well‐known in the statistical literature, is to replace the sample mean with a measure of location having a standard error that is relatively unaffected by heavy tails and outliers. One possibility is to use the trimmed mean. This paper describes three such multiple comparison procedures and compares them to two methods for comparing means.
Application of Random Coefficient Regression Model to Myopia Data: A Case Study
Authors: Möttonen Jyrki , Oja Hannu , Krause Ulf , Rantakallio Paula 
Published: May 2007

AbstractA one‐year birth cohort from Northern Finland has been followed up since 1966. As a part of this study, we are in this paper concerned with analysing the progression of myopia (nearsightness) up to the age of 20 years. The random coefficient regression model was chosen for the analysis because of the large individual variation in the development of myopia. Maximum likelihood estimates for the parameters in the model were obtained via the expectation maximization (EM) algorithm. It is shown how the estimated model can be used to predict future observations for an individual using the previously recorded refractive error measurements as well as other relevant data on the patient in question.
Maximum Likelihood Estimation of Simultaneous Pairwise Linear Structural Relationships
Authors: Bolfarine Heleno , Rojas Manuel Galea 
Published: May 2007

AbstractThe problem of assessing the relative calibrations and relative accuracies of a set ofpinstruments, each designed to measure the same characteristic on a common group of individuals is considered by using the EM algorithm. As shown, the EM algorithm provides a general solution for this problem. Its implementation is simple and in its most general form requires no extra iterative procedures within the M step. One important feature of the algorithm in this set up is that the error variance estimates are always positive. Thus, it can be seen as a kind of restricted maximization procedure. The expected information matrix for the maximum likelihood estimators is derived, upon which the large sample estimated covariance matrix for the maximum likelihood estimators can be computed. The problem of testing hypothesis about the calibration lines can be approached by using the Wald statistics. The approach is illustrated by re‐analysing two data sets in the literature.
A Discrete Delta Method for Estimating Standard Errors for Estimators in Quantal Bioassay
Authors: Cobb E. Benton , Church J. D. 
Published: May 2007

AbstractA nonparametric discrete delta method for estimating standard errors of percentile estimators in quantal bioassay is described. A simulation study of confidence intervals for EDx in probit analysis shows the discrete delta method compared favorably with intervals based on maximum likelihood and also some parametric bootstrap methods.
Weighted Concordance Analysis
Authors: Tricot Jean‐Marie , Lepage Yves 
Published: May 2007

AbstractUsing the variance stabilizing technique, a product multinomial model is introduced to generate a new statistic to test observers' uncertainty in a weighted concordance analysis. Distance matrices which follow some specific rules are obtained by linear combinations of hierarchical distance matrices whose elements are equal to 0 or 1 and unit diagonal. The new statistic is compared with the kappa statistic interpreted by considering the covariance matrix generated by the data. By rewriting the test statistic in a barycentric form, one demonstrates how to modify the barycentric coefficients to derive an adequate measure of the interobserver agreement. The methods are illustrated using two examples.
Raking Kappa: Describing Potential Impact of Marginal Distributions on Measures of Agreement
Authors: Agresti Alan , Ghosh Atalanta , Bini Matilde 
Published: May 2007

AbstractSeveral authors have noted the dependence of kappa measures of inter‐rater agreement on the marginal distributions of contingency tables displaying the joint ratings. This paper introduces a smoothed version of kappa computed after raking the table to achieve pre‐specified marginal distributions. A comparison of kappa with raked kappa for various margins can indicate the extent of the dependence on the margins, and can indicate how much of the lack of agreement is due to marginal heterogeneity.
Optimal Unconditional Tables for Comparing Two Independent Proportions
Authors: Andrés, A. Martín , Sil Va Mato A. 
Published: May 2007

AbstractComparing two independent binomial proportions is quite a common problem in statistical practice. The unconditional method for doing so is more powerful than the conditional method (Fisher's exact test), but the computational difficulties of the former are much greater, and beyond the reach of most researchers. The solution adopted so far has been the publication of tables for critical regions, but the only ones that exist (MCDONALD et al., 1977; SUISSA and SHUSTER, 1985; and HABER, 1986) have certain limitations which prevent their general use (they are only valid for one‐tailed tests; they allow very limited values of sample size and α error, and they are not constructed using the most powerful version of the test). In this paper the authors present tables which do not contain these limitations and which are valid for α errors of 1%, 5% and 10% and for sample size of n1 ≦n2 ≦25 (beyond this figure, approximations may be used). They also illustrate the way to apply these tables (albeit in a conservative fashion) to the case of multinomial 2 × 2 trials.
Marked Point Process: Using Correlation Functions to Explore a Spatial Data Set
Authors: Goulard Michel , Pagès L. , Cabanettes A. 
Published: May 2007

AbstractThe relationship between the locations of the clumps of sprouts, some morphological characteristics of the clumps and the local soil environment in an old sweet chestnut coppice are studied. The theory of marked point process, which has not yet been used extensively in forestry studies, is shown to be adequate for the analysis of this type of spatial data. The marks correspond to morphological characteristics of the clumps: “diameter”, “number of sprouts”, “height at one year”, and “height at three years”. Several covariance functions are described which give a method for exploring the spatial relationships within the stand. Some of these functions are introduced for the first time in an actual statistical analysis.By using these functions, it is shown that the clumps are regularly distributed. The variables “diameter” and “number of sprouts” are strongly spatially negatively correlated, whereas the heights are slightly or not correlated. By categorising the individuals according to the mark values, it is shown that the small clumps tended to be aggregated in the gaps between medium and large clumps. Values of heights in the ties of the distribution are related as well as their spatial correlation to the local soil environment.
On Encoding Values for Data Recorded as X ≥ C
Authors: Lachenbruch Peter A. , Clements Philip J. , He Weizhong 
Published: May 2007

AbstractIn many medical and other contexts, an ordered variable is measured and the limits of measuring ability will be reached. In such cases, the data may be reported as X ≥ C. For example, in a cell count, a laboratory technician may report the data as “count ≥ 100.” If the data are a dependent variable, censored data methods are the standard techniques. However, if X is an independent variable, some methods need to be devised to handle the problem. A simple method is to encode the values X ≥ C to some value X0. A candidate for this is the conditional mean (or median) of X given X ≥ C. This paper gives some results, and examines some robustness questions for the proposed method.
Construction and Comparison of Two Receiver Operating Characteristic Curves Derived from the Same Samples
Authors: Le Chap T. , Lindgren Bruce R. 
Published: May 2007

AbstractReceiver operating characteristic (ROC) curves are used to describe the performance of diagnostic procedures. This paper proposes a simple method for the statistical comparison of two ROC curves derived from the same set of patients and the same set of healthy subjects. Generalization to studies involving more than two screening factors is straightforward. This method does not require the calculation of variances of the areas or difference of areas under the curves.
Augmented Partial Diallel Design for Estimating Combining Ability of Parents
Authors: Jaggi Seema , Agarwal K. N. 
Published: May 2007

AbstractThe Augmented Partial Diallel Cross (APDC) represents an intermediate position between the Complete Diallel Cross (CDC) and the Partial Diallel Cross (PDC) in which one or more primary lines are crossed with all the other lines but the lines of secondary interest form a PDC system. The method of sampling adopted for crosses of secondary lines is from arrangement of secondary lines on circumference of a circle. The mathematics for analysis of such APDC has been given systematically. The efficiency of estimates of general combining ability (g.c.a.) effects obtained from APDC has been compared with that of Pederson's estimator and CDC. It is observed that there are four types of variances for g.c.a. effects where as for comparing specific combining ability (s.c.a.) effects there are large number of variances indicating that the design is totally unbalanced for s.c.a. comparisons.
A Simple Procedure for Constructing Experiment Designs with Incomplete Blocks of Sizes 2 and 3
Authors: Federer Walter T. 
Published: May 2007

AbstractIn order to maximize control of heterogeneity within complete blocks, an experimenter could use incomplete blocks of size k = 2 or 3. In certain situations, incomplete blocks of this nature would eliminate the need for such spatial types of analyses as nearest neighbor. The intrablock efficiency factors for such designs are relatively low. However, with recovery of interblock information, FEDERER and SPEED (1987) have presented measures of design efficiency factors which demonstrate that efficiency factors approach unity for certain ratios of the intrablock and interblock variance components. Hence with recovery of interblock information, even incomplete block designs with k = 2 or 3 have relatively high efficiency factors. The reduction in the intrablock error variance over the complete block error variance in many situations will provide designs with high efficiency.A simple procedure for constructing incomplete blocks of sizes 2 and 3 is presented. It is shown how to obtain additional zero‐one association confounding arrangements when v = 4 t, t an integer, and for v = pk, k ≤ p. It is indicated how to do the statistical analysis for these designs.
Comparing Trials with Multiple Outcomes: The Multivariate One‐Sided Hypothesis with Unknown Covariances
Authors: Frick Hans 
Published: May 2007

AbstractThe paper deals with a problem arising for tests in clinical trials. The outcomes of a standard and a new treatment to be compared are multivariate normally distributed with common but unknown covariance matrix. Under the null hypothesis the means of the outcomes are equal, under the alternative the new treatment is assumed to be superior, i.e. the means are larger without further quantification. For known covariance matrix there is a variety of tests for this problem. Some of these procedures can be extended to the case of unknown covariances if one is willing to accept a bias. There is, however, also an efficient unbiased test. The paper contains some numerical comparisons of these different procedures and takes a look on the minimax properties of the unbiased test.
Use of Phase for the Detection of Hidden Periodicites
Authors: Reschenhofer Erhard 
Published: May 2007

AbstractStandard tests for the detection of hidden periodicities in time series are largely ignored by applied workers. Various simple but inappropriate methods are used instead. Therefore a method is suggested which is both simple and appropriate but which requires the prior knowledge of certain characteristics of the suspected periodicity. For illustration, this method is applied to a set of data from a chronobiological study.
Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling
Authors: Lui Kung‐Jong 
Published: May 2007

AbstractThree simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F‐test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.
Indices of Disease Severity in Diseases that Cause Abscesses in Target Organs
Authors: Trajstman A. 
Published: May 2007

AbstractSome animal diseases cause variable numbers of abscesses of varying severity in target organs. In assessing the efficacy of vaccines developed to combat these diseases it is necessary to devise indices of disease severity that incorporate the number of abscesses in an animal and the severity scores of the abscesses. Three indices are defined and their relative merits are discussed. Some of the distributional properties of the indices are examined and their relevance to statistical analyses are discussed.
Statistical Tests for Signals in Categorial Temporal Data
Authors: Cannon Ann R. , Meeker William Q. 
Published: May 2007

AbstractThis paper describes methods for using categorical temporal data to detect differences in behavior between a treated group and a control group. The first‐level output from the data is typically a set of many different correlated test statistics comparing the two groups. In previous work, a decision was made by counting the number of significant individual tests and calibrating with bootstrap simulation. This article goes further, suggesting two possible alternative statistics: the sum of the squared individual test statistics and a Wald‐like combination of the individual test statistics. All three overall comparison statistics are defined and a method for computing critical values from simulated distributions using a bootstrap method is given. The use of all three methods is then demonstrated on each of three data sets. Finally, a simulated power study reveals that the Wald‐like statistic is much better than the other two, leading to the suggestion of its use in place of the other two statistics.
Modelling the Age‐Period‐Cohort Trend Surface
Authors: Lee Wen C. , Lin Ruey S. 
Published: May 2007

AbstractAge‐period‐cohort analysis of incidence and/or mortality data has received much attention in the literature. Though several authors seem to offer solutions to the non‐identifiability problem inherent in this kind of analysis, the constraints imposed lack sound biological bases and the interpretability of the parameters is in doubt. By introducing the axes of ‘adjusted’ age, period, and cohort variables in the age‐period‐cohort trend surface, the authors find that separate effects from these variables can be estimated and can be clearly interpreted. The constraint behind the procedure is also found to be mathematically simple and elegant. Since the method still lacks a biological foundation, it is best viewed as an adjunct to the graphical trend‐surface analysis rather than as a solution to the non‐identifiability problem. Previously published mortality data of prostate cancer is used to illustrate the methodology.
Symmetry and Asymmetry Models for Rectangular Tables
Authors: Kateri M. , Papaioannou T. 
Published: May 2007

AbstractThe models of complete, quasi and conditional symmetry as well as marginal homogeneity and diagonal asymmetry, applicable to square contingency tables are extended to non‐square ones. Several properties of the models are investigated and estimation and test theory is presented. The utility of the new proposed models is discussed and illustrated by reanalyzing classical data sets.