bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Dichotomous Response Variables in Teratology
Authors: Marubini E. , Leite M. L. Correa , Milani S. 
Published: May 2007

AbstractIn the recent biometrical literature the methods suggested to analyze dichotomous data arising from experiments testing the teratogenic effect of chemicals, rely upon the Beta‐Binomial distribution of the relative frequencies of response. This paper reports the results of a simulation study aiming at investigating the performance of logistic‐linear models based on the previously mentioned distribution in comparison to that of a two‐steps procedure based on a weighted Analysis of Variance (ANOVA). The weights are computed to make allowance of both the intralitter correlation and the number of fetuses varying from litter to litter.The results attained in this study and considerations emerging from perusing the toxicological literature, show that it appears sensibile to suggest the use of weighted ANOVA to process dichotomous responses in teratology.
The Comparison of Some Empirical Functions of Growth Using Pond Snail Lymnaea Stagnalis L. as an Example
Authors: Arambašić M. , Ristanović D. , Kalauzi A. 
Published: May 2007

AbstractThe experimental data of the linear embryonal and postembryonal growth of pond snail Lymnaea stagnalis L. have been estimated using logistic, polynomial, Gompertz's and Bertalanffy's functions of growth. The obtained results have shown that, based on the square error value, Gompertz function is, among all growth functions used, the most adequate for the estimation of our experimental data concerning embryonal growth and 5‐parameter logistic functions is the most suitable for the estimation of postembryonal growth data.
Selecting the Best Multinomial Cell‐Provided it is Better than a Control
Authors: Chen P. 
Published: May 2007

AbstractBechhofer and Turnbull (1978) considered the problems of selecting the best normal population, provided it is better than a standard for the case of known variances or equal but unknown variances. Wilcox (1984) considered the same selection goal for the case of unequal unknown variance and provided the appropriate probability equations and the necessary table. Under the same selection formulation (which we will describe formally in the following sections), this article studies a class of composite inverse sampling procedures for selecting the best multinomial cell that is better than a control cell with unknown cell probability. The procedures guarantee that (a) with probability at least P*0 (specified), no cell is selected when the largest cell probability is sufficiently less than the control and (b), with probability at least P*1 (specified), the cell with the largest probability is selected when its probability is sufficiently greater than the second largest cell probability and the control cell probability.
A Method of Estimation for Some Bivariate Discrete Distributions
Authors: Papageorgiou H. , Kemp C. D. 
Published: May 2007

AbstractAs a method of estimating the parameters of bivariate discrete distributions from sample data, maximum‐likelihood usually involves iterative procedures which are complicated and relatively time‐consuming even on modern computers. Simple moment estimators, though quick and easy are, however, often inefficient and so alternative procedures have been investigated.In the present paper we introduce a simple estimation procedure which utilizes both marginal and conditional means, using the bivariate Poisson, negative binomial, Hermite and Neyman A distributions as illustrations. In addition, the bivariate negative trinomial distribution is fitted to a set of human family data and the correlation between the numbers of two types of children in a family is examined.
The Treatment of Missing Values in Logistic Regression
Authors: Fung Karen Yuen , Wrobel Barbara A. 
Published: May 2007

AbstractThe efficiencies of the estimators in the linear logistic regression model are examined using simulations under six missing value treatments. These treatments use either the maximum likelihood or the discriminant function approach in the estimation of the regression coefficients. Missing values are assumed to occur at random. The cases of multivariate normal and dichotomous independent variables are both considered. We found that in general, there is no uniformly best method. However, mean substitution and discriminant function estimation using existing pairs of values for correlations turn out to be favourable for the cases considered.
An Empirical Power Comparison of Three Tests of Exponentiality Under Mixture‐ and Outlier‐Models
Authors: Balakrishnan N. , Ambagaspitiya R. S. 
Published: May 2007

AbstractWe present the results of an empirical power study of three prominent goodness‐of‐fit tests for exponentiality due to Shapiro and Wilk (1972), Durbin (1975), and Tiku (1980) by considering the mixture‐ and the outlier‐ exponential models as alternatives. This study is on similar lines as those of Dyer and Harbin (1981) and Balakrishnan (1983). We show that Tiku's test is on the whole considerably more powerful than the other two tests.
Mixtures of Distributions by the Poisson Distribution of OrderK
Authors: Philippou A. N. 
Published: May 2007

AbstractThe Poisson‐binomial, the Poisson‐negative binomial (or Pascal) and Neyman's Type A distribution, which are Poisson mixtures of the binomial, the negative binomial and the Poisson distribution, respectively, have received a lot of attention in statistical literature [see e.g. Katti and Gurland (1961, 1962), Anscombe (1950), and Neyman (1939)]. In the present paper, their respective generalizations are introduced and briefly studied, when the Poisson distribution of orderk[see Philippou (1983), Philippou, Georghiou and Philippou (1983), and Charalambides (1986)] replaces the Poisson distribution in its mixing role.
A Single Compartment Quantal Response Model with a Renewal Type Input Process and IID Releases
Authors: Huang Wen‐Jang , Huang Mong‐Na Lo 
Published: May 2007

AbstractWe deal with a single compartment quantal response model, where unlike the previous models, which do not have any input after the administration of a single doseZ(0)=zat time t=0, we allow inputs of doses after time t=0. More precisely, the system uses the (s,S) input policy as in inventory models, and has IID releases. Also when the amount of dose in the subject reaches 0, there is a probabilitypto stop having input thereafter. Among other results, the probability that the subject never responds and the expressions for some quantities of interest are obtained.
Simulations to Determine the Mean and Variance of the Point‐Object Analogue of the Clark‐Evans Statistic
Authors: Doguwa S. I. , Upton G. J. G. , Doguwa Sani I. 
Published: May 2007

AbstractDoguwa and Upton (1988) propose edge corrections for the mean and variance of the average distance X, between a sampling point and the nearest object in a spatial point pattern for the case of a regular grid of sampling points. However, their edge corrections are not applicable to circular sampling windows. This paper extends the range of application of X, by providing its revised mean and variance for use with circular regions.
Treatment Response Predicted from Polarity Patterns in Depressives by Complementary Prediction CFA
Authors: Havránek Tomáš , Lienert G. A. 
Published: May 2007

AbstractA sample of N = 32 depressive patients was observed as to their polarity sequences defined as 4 binary independent variables. After Lithium treatment the dependent variable was a yes‐no improvement rating. Nonparametric evaluation of the multivariate regression was made by complementary version of predictive configural frequency analysis. It was confirmed that the ocurrence of manic‐depressive episodes prior to treatment was favor of improvement, as hypothesized by the clinician. A construction of exact tests is suggested.
Some Further Remarks on Robust Selection of Variables in Discriminant Analysis
Authors: Krusińska Ewa , Liebhart Jerzy 
Published: May 2007

AbstractA robust method of selecting variables with the greatest discriminatory power is presented in the paper. It is based on the robustified Wilks A statistic and can be applied in a multi‐group discrimination problem. An application to some respiratory disease data together with a comparison of the classical procedure is also given.
Statistical Analyses of Twins Birth Data from a Nigerian Sample
Authors: Lawal H. B. 
Published: May 2007

AbstractIn this paper, both the linear logistic model and its analogous linear model (weighted least squares) are fitted to twin birth data from a Nigerian sample. The logits of the observed perinatal mortality rates are fitted against the birthweight of breech infants for both first born and second born twins. Results show that a quadratic response model fits the data very well, and that the WLS procedure gives a better fit. The results further show that breech births necessarily result in 7.7% and 11.2% mortality rates respectively for first born and second born twins. The results of a log‐linear model analysis on the 2×2×4 contingency table formed by the factors, ‘mode of birth’, and twins with the response variable ‘Apgar Scores’‐an index of morbidity‐also show that both factors play significant roles in explaining the variation of the response variable. It was found that the most important factor effecting the ability of a twin infant to survive as measured by the Apgar scores is the variable ‘mode of birth’ (vertex or breech). In other words, a vertex first twin infant has the best survival chance.
Compound Regression Models for Ordered Categorical Data
Authors: Tutz Gerhard 
Published: May 2007

AbstractA general class of sequential models for the analysis of ordered categorical variables is developed and discussed. The models apply if the ordinal response may be subdivided into two or more meaningful sets of response categories. The parametrization explicitly makes use of this subdivision. The models furnish a linear alternative to non‐linear models which incorporate a scale parameter. They are shown to be special cases of multivariate generalized linear models. Applications are discussed with the use of several examples.
A Probabilistic Approach to the Construction of Competing‐Risk Life Tables
Authors: Hsieh John J. 
Published: May 2007

AbstractThis paper aims to indentify net and partial‐crude probabilities in the competing‐risk life table context, by using probabilistic approaches. Five types of lifelength random variables are defined to formulate these nonidentifiable probabilities. General expressions for net and partial‐crude probabilities are first derived under independent risks assumptions. Two sets of explicit formulas for estimating the net and partial‐crude probabilities are then derived in terms of the identifiable overall and crude probabilities by making the additional assumption of piecewise uniform distribution of the lifelength random variables. A study of the degree to which nonidentifiability can affect the net and partial‐crude probabilities in a variety of situations is developed. An example from cross‐sectional studies is employed to illustrate the methodology developed.
A Martingale Approach to the Investigation of the Duration of a Mild Epidemic
Authors: Biswas Suddhendu , Thomas Mariamma 
Published: May 2007

AbstractThe present paper is an attempt to evolve a simple methodology to obtain the steady state solution of the duration of a mild epidemic (like conjunctivitis, for which the period of sickness is about a week and the period of immunity following recovery is comparatively large) and also the intensity of the epidemic measured by the number of infections during the complete spell of the epidemic. The methodology consists of constructing Martingales based on subcritical and supercritical forms of a Simple Branching Process; and obtaining the stopping time enabling to evaluate the expected duration of the epidemic and the sampling variance together with the intensity of the epidemic.
New Procedure for Selection of Variables in Location Model for Mixed Variable Discrimination
Authors: Krusińska Ewa 
Published: May 2007

AbstractA new method for the choice of variables with the greatest discriminatory power in the location model for mixed variable discriminant analysis is presented in the paper. The procedure based on the multivariate discriminatory measure enables a simultaneous reduction of the number of discrete and continuous variables. The introduced criterion can be used for both optimal or step‐wise selection of variable subset. As an example the results of the stepwise variable selection for some medical data are presented in the paper.
A Non‐metric Procedure for Transforming Dissimilarities to Euclidean Distances Useful in Numerical Taxonomy and Ecology
Authors: Lefkovitch L. P. 
Published: May 2007

AbstractBecause (a) in agglomerative cluster analysis, it is the smallest dissimilarities which are used, (b) in numerical ecology, little or no information is given about the resemblance between two localities if there are very few (or no) species in common, (c) for a given dissimilarity, the number of ways two objects can differ in the states shown by their attributes is small for small dissimilarities, and disproportionately larger for larger dissimilarities, (d) the major axes in principal coordinates analysis are determined by the largest dissimilarities, which from (a–c) are the least informative, and (e) the ‘orsesho’ pattern often shown by two‐dimensional scalings of dissimilarities, it is concluded that the largest dissimilarities should be replaced by values determined from the smallest.The proposal is to retain the dissimilarities corresponding with the edges in the relative neighbourhood graph, and to replace the remaining by the shortest paths on the dissimilarity‐weighted graph. The new dissimilarities, which are linearly related with the retained subset, are shown to be Euclidean, and usually the effective dimensionality is reduced in comparison with the original set. The internal disposition of distinct subsets of objects is little affected, but any distinct subsets tend to be further separated.By contrast, if the smallest dissimilarities represent random differences, while the larger subset represents those which are systematic, it is the latter which should be retained. The notion of the relative external graph is introduced, and the procedures required to obtain this, and to replace the deleted empirical smallest dissimilarities briefly described. However, this results in an increase in the effective dimension, changes in the internal disposition of distinct subsets, and reduction in their separation.–Two numerical examples, based on empirical data, illustrate some of the consequences of the transformations.
Two‐Stage Procedures for Comparing Treatments with a Control: Elimination at the First Stage and Estimation at the Second Stage
Authors: Bechhofer Robert E. , Dunnett Charles W. , Tamhane Ajit C. 
Published: May 2007

AbstractWe consider the problem of comparing a set of p1 test treatments with a control treatment. This is to be accomplished in two stages as follows: In the first stage, N1 observations are allocated among the p1 treatments and the control, and the subset selection procedure of Gupta and Sobel (1958) is employed to eliminate “inferior” treatments. In the second stage, N2 observations are allocated among the (randomly) selected subset of p2(≤p1) treatments and the control, and joint confidence interval estimates of the treatment versus control differences are calculated using Dunnett's (1955) procedure. Here both N1 and N2 are assumed to be fixed in advance, and the so‐called square root rule is used to allocate observations among the treatments and the control in each stage.Dunnett's procedure is applied using two different types of estimates of the treatment versus control mean differences: The unpooled estimates are based on only the data obtained in the second stage, while the pooled estimates are based on the data obtained in both stages. The procedure based on unpooled estimates uses the critical point from a p2‐variate Student t‐distribution, while that based on pooled estimates uses the critical point from a p1‐variate Student t‐distribution. The two procedures and a composite of the two are compared via Monte Carlo simulation. It is shown that the expected value of p2 determines which procedure yields shorter confidence intervals on the average. Extensions of the procedures to the case of unequal sample sizes are given. Applicability of the proposed two‐stage procedures to a drug screening problem is discussed.
A Note on Measures of Multivariate Kurtosis
Authors: Koziol James A. 
Published: May 2007

AbstractWe propose a measure of multivariate kurtosis suggested from Mardia's measure of multivariate skewness b1,p, and examine its relationship both to Mardia's measure of multivariate kurtosis b2,p, and to a smooth test of multivariate kurtosis Ǔ42.
On the E‐Optimality of Block Designs with Unequal Block Sizes
Authors: Brzeskwiniewicz Henryk 
Published: May 2007

AbstractIn this paper an inequality for the smallest positive eigenvalues of theC‐matrix of a block design are derived. This inequality is a generalization of a result by Constantine (1982) to the case of unequal block sizes. On the basis of the above result a certainE‐optimality criterium of block designs is given. Furthermore coefficientedhas been introduced which permits to assess how close the block design is from the optimal one.
Some Remarks on the Estimation of the Ratio of the Expectation Values of a Two‐dimensional Normal Random Variable (Correction of the Theorem of Milliken)
Authors: Guiard V. 
Published: May 2007

AbstractIt is possible to show that the theorem of Fieller yields an exact confidence region derivable from the likelihood ratio test. The statement of Milliken (1982) that this confidence region is conservative is refuted. Bounds for the conditional confidence coefficient under the condition that the confidence region is a “meaningful” confidence interval are given.
Reliability Models in Cancer Epidemiology
Authors: Becker Nikolaus 
Published: May 2007

AbstractA special class of reliability models called “cumulative damage models” is introduced and demonstrated that it very well matches the view of epidemiology on carcinogenesis. This new approach helps to overcome conceptual problems of existing models and, moreover, allows among other things the incorporation of mathematical representatives for host responses which has not been achieved so far by other models. The paper outlines first results concerning descriptive epidemiolo‐gical data as well as data on special exposure histories or applications to dose‐response considerations in animal experiments. The new mathematical issue implies partially substantially differing interpretations of observed data, compared to existing models, and promises that cumulative damage models will be a powerful tool for theoretical epidemiological investigations in the future.
Genetic Analysis of Line x Tester Progenies Compared in Orthogonally Supplemented Efficiency Balanced Incomplete Block Designs
Authors: Hanna Anita Dobek , Kaczmarek Zygmunt , Kielczewska H. 
Published: May 2007

AbstractThe theory which analyses the progenies of line X tester crossing procedure and one group of homozygous parents is presented. This analysis allows to conclude on genetics of a quantitative character of parents included in the experiment. The statistics like variance among parents, mean variance of progenies of lines, variance of tester progeny means and covariance of testers with means of their progenies can be derived. On that base one can get four different genetic parameters of variance. In a special case of experiment, it is possible to test the significance of additive variance.
Estimators Asymptotically Minimax in Wide Sense
Authors: Vajda Igor 
Published: May 2007

AbstractEstimators of location are considered. Huber (1964) introduced estimators asymptotically minimax on the set 𝔖 of all regular M‐estimators, for a given contamination ε and for the set Q of all regular symmetric alternative data sources. We extend his concept by admitting arbitrary sets 𝔖 of regular M‐estimators and arbitrary sets Q or regular symmetric alternative sources, and also by replacing the singletons [ε] ⊂ (0, 1) by arbitrary subsets 𝔖 ⊂ (0, 1). The resulting estimator cannot in general be evaluated explicitly. But for finite T it exists and, if 𝔖 and Q are finite too, it may be chosen by a computer. This extra burden is justified in some cases since more than 100% relative efficiency gain against all Huber's Hk is achievable in this manner. Such gains are achieved for a nontrivial family Q by the estimator proposed in Vajda (1984), with redescending influence curve, which is shown to be asymptotically minimax in wide sense.
Leverage in Bayesian Regression
Authors: Steece Bert M. 
Published: May 2007

AbstractUsing the concept of an extended data set (Zellner, 1986), we derived the projection or hat matrix for Bayesian regression analysis. The hat matrix shows how much influence or leverage the observed responses and the prior means have on each of the posterior fitted values. The amount of leverage associated with the observed data is shown to be a monotonically decreasing function of the ratio of the process variance to the prior variance. Additional properties of the Bayesian hat matrix are discussed. Two illustrative examples are presented.
Correction of Eye‐estimation by Using Shrunken Predictors
Authors: Bouza C. N. , Allende S. M. 
Published: May 2007

AbstractThe eye‐estimation method is widely used in practice. Several agronomic and biological measures are currently estimated by this method. If a simple linear regression is the kernel model a shrinkage technique can be used for correcting the bias associated with this method.Two predictors of the population total are proposed and the corresponding model‐based errors are deduced.A simulation study fixes the behaviour of the predictors.
Third‐order Minimax Designs for the Difference Between Two Estimated Responses
Authors: Huda S. 
Published: May 2007

AbstractMinimization of the variance of the difference between estimated responses at two points maximized over pairs of points in the region of interest is taken as the design criterion. Optimal third‐order designs are derived for spherical co‐centric regions of experimentation and interest with some restrictions imposed on the pairs of points under consideration.
The Influence of the Incubation Period on Qualitative Aspects of the Spread of AIDS
Authors: Lasser R. , Obermaier J. 
Published: May 2007

AbstractBased on a simple stochastic model the influence of the incubation period of the HIV‐infection on some qualitative aspects of the spread of AIDS is studied. A critical ‘nfection rat’ is calculated in dependence on parameters of the incubation period density function.
Joint Confidence Sets in Multiple Dilution Assays
Authors: Jensen D. R. 
Published: May 2007

AbstractLet {Q1, …,Qk} be the potencies ofksubstances relative to a standard in a multiple dilution assay. Joint confidence bounds for these are given with confidence coefficient at least 1‐α. These bounds are easily interpreted; they appeal to available tables; they improve Scheffe's bounds; they are based on applicable probability inequalities together with extensions of Fieller's theorem; and they are genuinely nonparametric. The procedures are illustrated using data from parallel‐line and slope‐ratio assays.
On the Distribution of Straddling Birth Intervals
Authors: Yadava R. C. , Pandey Arvind 
Published: May 2007

AbstractBased on some simplified assumption relating to the human reproduction process, probability models for the study of straddling birth intervals have been discussed in this paper. One of the models for illustration has been applied to an observed set of data taken from a sample survey on maternity histories of women in Varanasi.