bluuebunny/crossref_metadata_2025 huggingface dataset:
Zur Erhebung des Einflusses von Wildtieren auf die Waldverjüngung | Investigation of the Influence of Wild Animals on Forest Regeneration
Authors: Rüegg Dani
Published: May 2007

The existing information on the influence of wild animals on forest regeneration is an important basis for solution-finding for the ever-increasing problems of regeneration. Sufficient expert estimations allow the problematic areas to be recognised at a regional level and to be separated from the others. Indicator areas of the problematic sites, which should amount to at least 30 ha, the woody plants assessed according to tree species, size class and feeding damage to tips during the vegetation period of the previous year and the resting period directly before the assessment time in spring, can be counted on systematically distributed, permanent, simple sample circles. The interpretation of regenerative parameters should be based particularly on the intensity of feeding damage and its limited values according to EIBERLE and NIGG (1987) as well as the stem numbers. Pairs of comparable areas, one fenced and one unfenced respectively,are suitable as sample subjects for selective small-scale site observation. They present information on the influence of wild animals on indicator areas of the size of a stand or of a micro-site favourable to regeneration.
Schwerpunktbejagung | Area Focused Hunting
Authors: Odermatt Oswald
Published: May 2007

Spatial and temporal differences in game density comply with the dynamics of nature. Area-focused hunting could have its effects on similar conditions. By means of permanent, massive hunting pressure, a significantly thinned game density on a limited area is striven for. From time to time, the mountain forest is in need of phases of poor game density for profound forest regeneration.
A non‐ancestral RPGR missense mutation in families with either recessive or semi‐dominant X‐linked retinitis pigmentosa
Authors: Banin Eyal , Mizrahi‐Meissonnier Liliana , Neis Ruhama , Silverstein Shira , Magyar István , Abeliovich Dvorah , Roepman Ronald , Berger Wolfgang , Rosenberg Thomas , Sharon Dror
Published: May 2007

Most X‐linked diseases show a recessive pattern of inheritance in which female carriers are unaffected. In X‐linked retinitis pigmentosa (XLRP), however, both recessive and semi‐dominant inheritance patterns have been reported. We identified an Israeli family with semi‐dominant XLRP due to a missense mutation (p.G275S) in the RPGR gene. The mutation was previously reported in two Danish families with recessive XLRP. Obligate carriers from the two Danish families had no visual complaints and normal to slightly reduced retinal function, while those from the Israeli family suffered from high myopia, low visual acuity, constricted visual fields, and severely reduced electroretinogram (ERG) amplitudes. The disease‐related RPGR haplotype of the Israeli family was found to be different from the one found in the two Danish families, indicating that the mutation arose twice independently on different X‐chromosome backgrounds. A series of genetic analyses excluded skewed X‐inactivation pattern, chromosomal abnormalities, distorted RPGR expression level, and mutations in candidate genes as the cause for the differences in disease severity of female carriers. To the best of our knowledge, this is the first detailed analysis of an identical mutation causing either a recessive or a semi‐dominant X‐linked pattern of disease in different families. Our results indicate that an additional gene (or genes), linked to RPGR, modulate disease expression in severely affected carriers. These may be related to the high myopia concomitantly found in affected carriers from the Israeli family. © 2007 Wiley‐Liss, Inc.
Successful neurological outcome of a child with classical phenylketonuria and acute lymphoblastic leukemia: A 7‐year follow‐up
Authors: Wang Cheng , Camfield Carol S. , Fernandez Conrad V. , Hurley Terry , Campbell Karen
Published: May 2007

We report on the medical management and outcome of a child with classical phenylketonuria (PKU) who developed acute lymphoblastic leukemia (ALL). Chemotherapy began at 24 months of age. Initial problems associated with treatment lead to remarkable releases of phenylalanine, a neurotoxin. Causes included increased catabolism secondary to tumor lysis and chemotherapy, as well as infection, intermittent fasting and anorexia. Medical management involved daily monitoring of Phe levels and major changes in the amount of medical formula and the intake of protein containing foods in the diet. The child is currently in remission from ALL and has a normal neurodevelopmental outcome 7 years after the ALL diagnosis. © 2007 Wiley‐Liss, Inc.
Synthesis, characterization and in vitro cytotoxicity of homobimetallic complexes of palladium(II) with 2‐thiouracil ligands. Crystal structure of [Pd2(TU)(PPh3)3Cl2]
Authors: Shaheen Farkhanda , Badashah Amin , Gielen Marcel , Marchio L. , de Vos Dick , Kaleem Khosa M.
Published: May 2007

Square planar metallic and homonuclear bimetallic complexes of Pd(II) with 2‐thiouracil (HTU) and organophosphines have been synthesized and characterized by FT‐IR and multinuclear 1H, 13C, 31P NMR spectroscopy. The thiouracil ligand TU acts as bidentate, is bound through the thioxo moiety and the endo amino group and forms a bridge between a PdCl(R3P) and a PdCl(R3P)2 moiety [R3P = Ph3P (o‐tolyl)3P, ClPh2P] in the homonuclear bimetallic complexes. The square planar geometry around Pd(II) has been confirmed for these complexes by a single‐crystal X‐ray diffraction study of compound 1, [Pd2(TU)(PPh3)3Cl2]. These compounds were also screened against human tumor cell lines and showed promising in vitro cytotoxicity. Copyright © 2007 John Wiley & Sons, Ltd.
Synthesis of polyacrylamide‐wrapped carbon nanotubes and their lubrication properties as water‐based fluids
Authors: Liu Yifeng , Guan Wenchao , Li Xuefeng , Huang Mingxing
Published: May 2007

Carbon nanotubes (CNTs) wrapped by polyacrylamide (PAM) were synthesized through the insitu free‐radical polymerization of acrylamide in the presence of the CNTs. Transmission electron microscopy was used to characterize the synthetic CNTs/PAM. This product dissolved easily in water. The effects of the synthetic product as an additive on the load‐carrying capacity and antiwear behavior of a water‐based fluid were investigated with a four‐ball tribotester. The worn surface images of the steel balls were observed by scanning electron microscopy. The results showed that CNTs/PAM at a certain concentration in the base stock effectively raised the load‐carrying capacity and antiwear ability. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007
Comparative analysis of the structural parameters and strength properties of polyacrylonitrile fibers containing ceramic nanoadditives
Authors: Mikołajczyk Teresa , Boguń Maciej , Rabiej Stanisław
Published: May 2007

The structural parameters and strength properties of three types of new‐generation precursor polyacrylonitrile fibers are comparatively analyzed. These fibers, after the carbonization process, can be used as implants supporting the process of bone reconstruction. They are characterized by a high tenacity ranging from 21 to 41 cN/tex. Tests and measurements have shown that the presence of nanoadditives causes a clear increase in the degree of fiber crystallinity. Moreover, the tenacity of the fibers can be considerably increased by the grinding of nanoadditive agglomerates with ultrasound. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007
Inherent biases in decision support systems: the influence of optimistic and pessimistic DSS on choice, affect, and attitudes
Authors: Korhonen Pekka , Mano Haim , Stenfors Sari , Wallenius Jyrki
Published: May 2007

This study investigates the influence of a decision aid on decision makers' model‐based choices, emotions during the use of the model, and attitudes towards the model. A time allocation decision model was biased to purposefully provide optimistic or pessimistic criterion levels, on which subjects based their allocations. The results of our experiment indicate that the degree of “optimism” and “pessimism” inherent in the decision model had a significant impact on the decision maker's choices of criterion values, with optimism leading to higher criterion level choices and pessimism to lower levels. Furthermore, compared to pessimistic models, optimistic models significantly improved the decision makers' emotional states and, to some degree, their attitudes towards the decision aid. The implications of these conscious and sub‐conscious influences on decision makers' choices, emotions, and attitudes are discussed and the need for model‐builders and users to be aware of them is highlighted. Copyright © 2007 John Wiley & Sons, Ltd.
An Algorithm for Calculation of n‐Dimensional Nonlinear Dependencies – Behaviour Tests on Rats
Authors: Kniepert E. , Kniepert A.
Published: May 2007

The evaluation of the data obtained during the behaviour tests always leads to the problem of multiple correlation, very often with non‐linear dependencies on the target. All mathematical and statistical procedures that have been used so far are based on the assumption of an equation for the desired correlation for which parameters and related statistical equivalents are determined eventually. The MODAK system applied here (MODAK = algorithms of modelling for the calculation of multi‐dimensional non‐linear mathematical models) breaks down a complex correlation into individual dependencies in a mathematical and statistical way and selects suitable equations for each of them independently and determines the corresponding parameters. The numerical example evaluates data of behaviour tests on rats.

First results obtained on the correlations of various behaviour tests indicate both the possibility of selecting suitable tests independent of each other and a better interpretation of the observed patterns of behaviour taking into account the interrelations between the tests.

In addition, MODAK is a method which can be applied as a matter of course in a general way to all cases which call for the reduction and analysis of data occurring in process and system analysis and in the evaluation of test results requiring statistical modelling. So far, MODAK applications range from engineering sciences to medicine.
A Method for Analyzing Nonlinear Models When the Data are from a Split‐plot or Repeated Measures Design
Authors: Schaff D. A. , Milliken G. A. , Clayberg C. D.
Published: May 2007

Statistical methods are described which can be used to compare treatments where the response model is nonlinear and the experimental design includes split‐plots or repeated measures. The nonlinear analysis of covariance is described for a two‐way treatment structure in a split‐plot design structure, the usual split‐plot experimental design. Evaluating heat tolerance in common beans as a function of temperature is used as an example to demonstrate the methodology.
Quasi‐fixed Points w.r.t. the Height Growth Curve
Authors: Masuyama M.
Published: May 2007

When height growth curves are linearized, these lines are nearly concurrent after the growth spurt (Masuyama, 1979, 1982b, 1983), i.e. there exists a nearly fixed point, which seems to correspond to the upper limit of the growth of the mean person. On other hand, before the spurt, there seems to exist a nearly fixed point on the mean distance‐velocity curve between 4 and 6 years of age. To grasp easily the existence of nearly fixed point, instead of many straight lines surrounding this point, we represent them dually by many points surrounding a straight line.
Sample Size Requirements in Studies of the Etiologic Fraction
Authors: Smith Judith A. , McHugh R. B.
Published: May 2007

This paper outlines methods of determining sample size for epidemiologic research in studies of the etiologic fraction. The basic model with a dichotomous disease and a single dichotomous exposure factor is considered. To determine sample size, the researcher must specify: the magnitude of the etiologic fraction ε to be detected as statistically significant, the level of significance α, the power 1 ‐ β of the test, p the proportion of the population exposed to the risk factor and R the proportion of the population with the disease. Sample size formulas and tables are presented for the case‐control, cohort and cross‐sectional designs. Optimal allocation considerations are examined to minimize cost for a specified power. Extensive use is made of Walter's results concerning the asymptotic variance of the maximum likelihood estimator of the etiologic fraction for the three epidemiologic study designs.
Profile Analysis of Variance as a Tool for Analyzing Correlated Responses in Experimental Ecology
Authors: Simms E. L. , Burdick D. S.
Published: May 2007

In ecological studies experiments are often designed in which the variables to be compared are not statistically independent. Examples include repeated measures of the same response by the same individual at different times, measurement of several traits on the same individual, and measurements taken from two or more types of organisms present together in the same experimental unit (e.g.) plot, cage, pond, etc.). This type of design violates several assumptions of the standard analysis of variance. These assumptions are examined and profile analysis, a modification of the standard analysis of variance which does not depend upon these assumptions, is presented. Simple instructions for performing profile analysis of variance using two common statistical packages for mainframe computers are provided in an appendix.
Generalized Walker‐Duncan Procedure for Obtaining Maximum Likelihood Estimates of Parameters of Logistic Discriminant Function
Authors: Keusińska Ewa
Published: May 2007

A recursive method of obtaining the maximum likelihood estimates of the parameters of the quadratic logistic discriminant function is presented. This method is an extension of the Walker and Duncan procedure (1967) proposed for the linear logistic discriminant function in a dichotomous case. A generalization of the method to the problem of discrimination between several populations is also given in the paper. It works for both linear and quadratic logistic discriminant function. After an estimation of the parameters of the logistic function a classification can be performed. An example of application of the method to automatic diagnosis of some respiratory diseases is presented. Comparison with the standard procedures used for the estimation is done by a short simulation study.
A Robust Test for Multi‐Sample Location Problems with Unequal Group Variances and Nonnormality
Authors: Tabatabai M. A. , Tan W. Y.
Published: May 2007

A robust test (to be referred to as M* test) is proposed for testing equality of several group means without assuming normality and equality of variances. This test statistic is obtained by combining Tiku's MML robust procedure with the James statistic. Monte Carlo simulation studies indicate that the M* test is more powerful than the Welch test, the James test, and the tests based on Huber's M‐estimators over a wide range of nonnormal universes. It is also more powerful than the Brown and Forsythe test under most of nonnormal distributions and has substantially the same power as the Brown and Forsythe test under normal distribution. Comparing with Tan‐Tabatabai test, M* is almost as powerful as Tan‐Tabatabai test.
Robust Hotelling‐Type T2 Statistics
Authors: Tiku M. L. , Balakrishnan N.
Published: May 2007

To test an assumed mean vector, and to test the equality of two mean vectors, robust statistics are developed which have exactly the same form as the Hotelling T2 statistics. These statistics are shown to have remarkable type I error robustness and power.
Use of Ranks in Comparisons of Variability in the Non‐Normal Populations
Authors: Rai S. C. , Sarup Shanti
Published: May 2007

A method of analysis for comparing the variability of two samples drawn from two populations has been developed. The method is also suitable for the nonnumeric form of data. A test based on ordered observations for testing the null hypothesis of equality of two variances has been given. The test statistic is a function of the sum of ranks assigned to smaller size sample. Ranking procedure has been modified to depict the variability in the data by the sum of ranks. The null distribution of the test‐statistic has been worked out for small samples and it turns out to be chi‐square distribution for large samples. The analytical procedure has been explained by a numerical example on the productivity and production of rice and wheat in India from 1950–51 to 1983–84.
Bayes's Theorem and the Analysis of Binomial Random Variables
Authors: Walters D. E.
Published: May 2007

A very practical application of Bayes's theorem, for the analysis of binomial random variables, is presented. Previous papers (Walters, 1985; Walters, 1986a) have already demonstrated the reliability of the technique for one, or two random variables, and the extension of the approach to several random variables is described. Two biometrical examples are used to illustrate the method.
On the Statistical Inference from Survival Experiments with Two Types of Failure
Authors: Rachev S. T. , Yakovlev A. Yu. , Kadyrova N. O. , Myasnikova E. M.
Published: May 2007

Formulated in terms of latent failure times a survival model with two dependent competing risks is considered. Using this model, it is possible to introduce the probabilistic characteristics of each type of failure contribution to the joint effect of two damaging agents. Confidence bounds for such characteristics are given.
On Generalized Log‐Logistic Model for Censored Survival Data
Authors: Singh Karan P. , Lee Carl M.‐S. , George E. Olusegun
Published: May 2007

In the analysis of survival data with parametric models, it is well known that the Weibull model is not suitable for modeling cases where the hazard rate is non‐monotonic. For such cases, log‐logistic model is frequently used. However, due to the symmetric property of the log‐logistic model, it may be poor for the cases where the hazard rate is skewed or heavily tailed. In this paper, we suggest a generalization of the log‐logistic model by introducing a shape parameter. This generalized model is then applied to fit the lung cancer data of Prentice (1973). The results seem to improve over those obtained by using the log‐logistic model.
Modelling Survival Data to Examine Length of Treatment Effectiveness in a Clinical Trial
Authors: Slymen Donald J.
Published: May 2007

In some clinical trials where the experimental treatment is found to be effective in increasing survival, an important question is how long should the patient remain under treatment. Although the trial may not be designed to specifically answer this question, comparisons of the hazard curves among the treatment groups can yield some useful information. The survival data may be modelled using a flexible set of hazard functions and specific models are then chosen for further examination. This paper illustrates the approach using data from the Beta‐Blocker Heart Attack Trial. Parametric and semi‐parametric models are fitted and likelihood methods are used to assess length of treatment effectiveness.
An Application of the Orthogonal Series Estimators in the Classification Of Mixed Variables
Authors: Wojciechowski T.
Published: May 2007

Suppose we have two general populations π1, π2. Each object belonging to the population πi, i = 1, 2 is characterized by a random vector X′ = (Z′, Y′), where Z is discrete and Y is continuous. On a certain element which is a member of a one of the two populations a realization π′0=(z′0, y′0) of the random vector X has been observed and we want to classify that element. One of the possible methods of doing it is to estimate the density functions of X in π1 and π2 and construct an estimated classification rule. In this paper the density estimates based on the orthogonal series (Hall, 1983) will be employed and the classification rule will be examined on a practical example.
The Statistical Analysis of Clustering of Events
Authors: Nagelkerke N. J. D. , Oskam S. , Fidler V. , Yzermans C. J.
Published: May 2007

The concept of clustering of events within elements of a population is explored. Test statistics for testing the null hypothesis of a Poisson process versus the alternative of clustering are developed and their conditional null expectation and variance are derived. An application to an EEG registration of an epilepsy patient is presented.
Analysis of Dichotomous Response Variables in Teratology
Authors: Marubini E. , Leite M. L. Correa , Milani S.
Published: May 2007

In 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

The 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

Bechhofer 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

As 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

The 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

We 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

The 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

We 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

Doguwa 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

A 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

A 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

In 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

A 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.
Goodness of Fit for the Geometric Distribution
Authors: Best D. J. , Rayner J. C. W.
Published: May 2007

A Neyman‐type smooth test of goodness of fit is derived for the geometric distribution. Some small‐sample critical points are given, with two examples.
Estimation Problems in Fitting Genetic Models to Familial Data
Authors: McGilchrist C. A.
Published: May 2007

Estimation of parameters in a genetic model can be very difficult using likelihood theory when there is no concise functional form for the likelihood function. An alternative method based on fitting the characteristic function is suggested and this method may be used on data with consistent familial composition.
A Probabilistic Approach to the Construction of Competing‐Risk Life Tables
Authors: Hsieh John J.
Published: May 2007

This 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

The 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

A 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

Because (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

We 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

We 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

In 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

It 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

A 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

The 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

Estimators 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

Using 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

The 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

Minimization 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

Based 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

Let {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

Based 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.
Statistical Measures of Instability in Crop Output
Authors: Rai S. C. , Sarup Shanti
Published: May 2007

Some aspects of methodological issues relating to statistical measures of instability in crop output has been discussed. Several existing techniques for detection and measurement of instability have been reviewed and some additions and modifications suggested. The application of distribution‐free tests has been indicated to test the significance of variability in the crop output over space and time. Various procedures have been explained by numerical data on crop output.
Robustness Study on Williams‐ and Shirley‐Procedure, with Application in Toxicology
Authors: Hothorn Ludwig
Published: May 2007

The first and second kind error behaviour of Williams and Shirley procedure under violation of normal distribution, variance homogenicity assumption and for selected expected value and sample size profiles are shown. The advantages of sequentially rejective modification were demonstrated.
Generalized Maximum Range Tests for Pairwise Comparisons of Several Populations
Authors: Royen Th.
Published: May 2007

A multiple comparison procedure (MCP) is proposed for the comparison of all pairs of several independent samples. This MCP is essentially the closed procedure with union‐intersection tests based on given single tests Qij for the minimal hypotheses Hij. In such cases where the α‐levels of the nominal tests associated with the MCP can be exhausted, this MCP has a uniformly higher all pair power than any refined Bonferroni test using the same Qij. Two different general algorithms are described in section 3. A probability inequality for ranges of i.i.d. random variables which is useful for some algorithms is proved in section 4. Section 5 contains the application to independent normally distributed estimates and section 6 the comparisons of polynomial distributions by multivariate ranges. Further applications are possible. Tables of the 0.05‐bounds for the tests of section 5 and 6 are enclosed.
A Closed‐form Jackknife Solution for the Behrens‐Fisher Problem
Authors: Schemper Michael
Published: May 2007

A simple, closed‐form jackknife estimate of the actual variance of the Mann‐Whitney‐Wilcoxon statistic, as opposed to the standard permutational variance under the test's null hypothesis has been derived which permits avoiding anticonservative performance in the presence of heterosce‐dasticity. The formulation given allows modifications of the exponential scores test, of censored data tests by Gehan (1965), Peto & Peto (1977) and Prentice (1978), of tests for monotonic τ association by Kendall (1962) and for tests of ordered k‐sample hypotheses. A Monte Carlo study supports recommendations for the jackknife procedures, but also shows their limited advantages in exponential scores and censored data versions. Thus, the paper extends results by Fligner & Policello (1981).
A Formula for the Gini Coefficient and its Decomposition
Authors: Tziafetas G. N.
Published: May 2007

This paper is concerned with the Gini coefficient as a concentration measure of the distribution. The proposed formula for the computation of the Gini coefficient allows its decomposition according to different sub‐groups of the initial population, either exactly or approximately.