bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some Adaptive Robust Estimators which Work with Real Data
Authors: Hill N. J. , Padmanabhan A. R. 
Published: May 2007

AbstractAn adaptive R‐estimator θA and an adaptive trimmed mean MAT are proposed. The performance of these and a number of other robust estimators are studied on real data sets, drawn from the astronomical, behavioural, biomedical, chemical, engineering and physical sciences. In the case of sets that can be assumed to have come from symmetric distributions, the best performer is θA. The next best performers are the Hodges‐Lehmann estimator, Bisquare (7.5) and Huber (1.5), in that order. MAT works well with all kinds of sets–symmetric or skewed. Extensions of these results to ANOVA and regression models are mentioned.
Designs Suited for Varietal Trials with Multiple Basals
Authors: Jain R. C. , Das M. N. 
Published: May 2007

AbstractDAS (1960) gave a method of construction of confounded balanced asymmetrical factorial designs of the type v × 22 by using BIB designs. In the present paper a method has been given for construction of balanced asymmetrical factorial designs of the type (v–t) × 22 by using truncated balanced incomplete block designs obtainable by omitting t treatments. Likewise, partially balanced asymmetrical factorial designs can also be obtained by omitting any particular treatment alongwith its first or second associate treatments from the v treatments of a PBIB design. We can get a large number of new designs not available in literature through this technique. These designs are well suited for varietal trials with multiple basals.
Restricted BLUP for Mixed Linear Models
Authors: McGilchrist C. A. , Aisbett C. W. 
Published: May 2007

AbstractA new estimation procedure for mixed regression models is introduced. It is a development of Henderson's best linear unbiased prediction procedure which uses the joint distribution of the observed dependent random variables and the unknown realisations of the random components of the model. It is proposed to replace the likelihood of the observations given the random components by the asymptotic likelihood of the maximum likelihood estimators and the prior distribution of the random components by a restricted prior distribution which is consistent with the usual restrictions placed on the random components when they are considered conditionally fixed.
A General Theory of Life Table Construction and a Precise Abridged Life Table Method
Authors: Hsieh John J. 
Published: May 2007

AbstractIn this paper we lay the foundation of life table construction by unifying the existing life table methods. We also present a new method of constructing current (period) abridged life tables. The proposed method produces more life talbe functions than other existing methods do. The development includes (1) a careful formulation and computation of age‐specific death rates, (2) derivation of a new set of formulas for computing the survivorship function from the observed age‐specific death rates and populations, (3) estimation of the main life table functions by spline interpolation, integration and differentiation, and (4) use of a quadratic and a Gompertz function to close the life table. The new abridged life table method features (i) improved accuracy, (ii) tolerance to observed age distributions with bulges and dents and (iii), together with the infant life table method of HSIEH (1985), coverage of the whole life span. The method is illustrated with construction of abridged life tables using Canadian data.
Comparing Survival Curves Using Rank Tests
Authors: Albers W. 
Published: May 2007

AbstractSurvival times of patients can be compared using rank tests in various experimental setups, including the two‐sample case and the case of paired data. Attention is focussed on two frequently occurring complications in medical applications: censoring and tail alternatives. A review is given of the author's recent work on a new and simple class of censored rank tests. Various models for tail alternatives are discussed and the relation to censoring is demonstrated.
Approximate Confidence Bounds for Ripley's Statistic for Random Points in a Square
Authors: Koen Chris 
Published: May 2007

AbstractConfidence envelopes for Ripley'sLfunction forNrandom points in the unit square were obtained by simulation. The 90, 95 and 99th percentiles of 1000 simulations are given in tabular form forNin the range 10 to 350. Results for a number of choices of the maximum interpoint distance are reported.
A Simple Testing Procedure “Control versus k Treatments” for One‐sided Ordered Alternatives, with Application in Toxicology
Authors: Hothorn L. , Lehmacher W. 
Published: May 2007

AbstractA simple testing procedure “control versus k treatments” for one‐sided ordered alternatives for univariate, continuous variables is given. With a simulation study both the first kind risk a and the power behaviour under several distributions, expected value profiles, sample sizes and a levels are shown.
Sampling Schemes for Studying Growth of Children
Authors: Singh Padam , Yadav R. J. 
Published: May 2007

AbstractEfficiency of linked cross‐sectional scheme has been compared with pure longitudinal schemes for generalised estimation of norm relaxing the condition of constancy of variances. The relevant theory of estimation has been developed and the expression for the optimum estimators alongwith their variances have been derived. The percentage gain in efficiency has been calculated. It has been observed that for higher values of Q, percentage gain in efficiency of proposed scheme over cross‐sectional is very high.
Linked Cross Sectional Schemes for Estimating Growth of Children
Authors: Singh Padam , Yadav R. J. 
Published: May 2007

AbstractFor estimation of growth, the efficiency of linked cross sectional scheme has been compared with pure longitudinal and cross sectional schemes. The relevant estimation theory has been developed and the expressions for the optimum estimators alongwith their variances have been derived. It has been observed that for estimation of growth, the linked cross‐sectional scheme has been observed to be less efficient as compared to pure longitudinal scheme but more efficient than pure cross‐sectional scheme.
Multivariate Polya and Inverse Polya Distributions of Orderk
Authors: Philippou A. N. , Tripsiannis G. A. 
Published: May 2007

AbstractMultivariate Polya and inverse Polya distributions of orderkare derived by means of generalized urn models and by compounding the type II multinomial and multivariate negative binomial distributions of orderkof PHILIPPOU, ANTZOULAKOSand TRIPSIANNIS(1990, 1988), respectively, with the Dirichlet distribution. It is noted that the above two distributions include as special cases a multivariate hypergeometric distribution of orderk, a negative one, an inverse one, a negative inverse one and a discrete uniform of the same order. The probability generating functions, means, variances and covariances of the new distributions are obtained and five asymptotic results are established relating them to the above‐mentioned multinomial and multivariate negative binomial distributions of orderk, and to the type II negative binomial and the type I multivariate Poisson distributions of orderkof PHILIPPOU(1983), and PHILIPPOU, ANTZOULAKOSand TRIPSIAN‐NIS(1988), respectively. Potential applications are also indicated. The present paper extends to the multivariate case the work of PHILIPPOU, TRIPSIANNISand ANTZOULAKOS(1989) on Polya and inverse Polya distributions of orderk..
Sparse Sampling and Maximum Likelihood Estimation for Boolean Models
Authors: Ayala G. , Ferrandiz J. R. , Montes F. 
Published: May 2007

AbstractA condition for practical independence of contact distribution functions in Boolean models is obtained. This result allows the authors to use maximum likelihcod methods, via sparse sampling, for estimating unknown parameters of an isotropic Boolean model. The second part of this paper is devoted to a simulation study of the proposed method.AMS classification: 60D05
The Reliability of Tests of Hypotheses when Overdispersed Logistic‐Linear Models are Fitted by Maximum Quasi‐Likelihood
Authors: Williams D. A. 
Published: May 2007

AbstractWhen overdispersed logistic‐linear models are fitted by maximum quasi‐likelihood hypotheses can be tested by comparing either the Wald statistic, or the quasi‐likelihood score statistic, or the quasi likelihood‐ratio statistic, with the approximating nullX2distribution. This paper reports a simulation study of the reliability of these tests. Some factors affecting their relative reliabilities are identified. An extended quasi‐likelihood ratio test is also considered.
Truncation of a Two Sample Sequential Wilcoxon Test
Authors: Skovlund Eva 
Published: May 2007

AbstractTo reduce the number of patients needed in a clinical trial, a sequential plan is sometimes used. This paper deals with the truncation of a sequential two sample Wilcoxon test which was originally an open plan (SKOVLUND and WALLØE, 1988). The truncated boundaries have been developed by stochastic simulation. These boundaries form a triangular continuation region. The simulated constants of the boundaries are presented in a table which may be used directly. Boundaries for truncation at 50, 100, 150 and 200 patients are developed. The chosen significance level may be 0.01, 0.025 or 0.05, and the power 0.95. To extend the applicability to other treatment differences than those tabulated, smooth curves are fitted to the simulated points. These make the test applicable to any treatment difference within the simulated range.
Notes on the Mack‐Wolfe and Chen‐Wolfe Tests for Umbrella Alternatives
Authors: Chen Y. I. 
Published: May 2007

AbstractIn this paper we find a class of umbrella alternatives for which the MACK‐WOLFE (1981) peak known test is optimal in the sense of Pitman efficiency. The asymptotic null distribution of the CHEN‐WOLFE (1989) statistic for the peak‐unknown umbrella alternatives problem is obtained. Some percentiles of the asymptotic distribution computed by simulation are presented.
Asymptotic Relative Efficiency of Some Jackknife Estimators of a Common Odds Ratio
Authors: Pigeot Iris 
Published: May 2007

AbstractIn the situation of several 2 × 2 tables the asymptotic relative efficiencies of certain jackknife estimators of a common odds ratio are investigated in the case that the number of tables is fixed while the sample sizes within each table tend to infinity. The estimators show very good results over a wide range of parameters. Some situations in which the estimators have low asymptotic relative efficiency are pointed out:.
Graphical Methods for Analysing Combination Effects in Dose‐Response Experiments
Authors: Guhr S. , Unkelbach H. D. , Pöch G. 
Published: May 2007

AbstractAn organbath experiment with bovine tracheal muscle strips with cumulative increases in concentrations of a substance A in the absence and presence of a fixed concentration of a second substance B is considered as an example for demonstrating graphical methods to analyse drug combination effects. The response of each strip is individually described and estimated by a nonlinear dose response curve. From the curves of the combined action theoretical curves of substance A are derived, which were expected if the combination effect was simple similar or independent, respectively. The first graphical method consists in comparing the derived curves for substance A with the curves for substance A directly fitted. It is cheeked by eye if the group of derived curves can clearly be distinguished from the group of directly fitted curves. The second graphical method differs from the first method in so far, as not the curves are visualized but the parameter vectors corresponding to them. In contrast to widely used analytical methods the proposed graphical methods allow to treat individual instead of averaged dose response relationships. The methods can help to decide if the combination effect may be considered as independent, simple similar or none of both.
On Fisher's Method of Combining p‐Values
Authors: Elston R. C. 
Published: May 2007

AbstractThe problem of combining p‐values from independent experiments is discussed. It is shown that Fisher's solution to the problem can be derived from a “weight‐free” method that has been suggested for the purpose of ranking vector observations (Biometrics 19: 85–97, 1963). The method implies that the value p = 0.37 is a critical one: p‐values below 0.37 suggest that the null hypothesis is more likely to be false, whereas p‐values above 0.37 suggest that it is more likely to be true.
Estimation of the Density ofGGiven Observations ofY=G+E
Authors: El‐Amraoui A. , Goffinet B. 
Published: May 2007

AbstractWe study the problem of estimating the density of a random variableG, given observations of a random variableY = G + E.The random variableEis independent ofGand its probability distribution function is considered as known. We build a family of estimators of the density ofGusing characteristic functions. We then derive a family of estimators of the density ofYbased on the model forY.The estimators are shown to be asymptotically unbiased and consistent. Simulations show that these estimators are better, as measured by integrated squared error, than the standard kernel estimators. Finally, we give an example of the use of this method for the detection of major genes in animal populations.
An Improvement of the Westlake Symmetric Confidence Interval
Authors: Müller‐Cohrs J. 
Published: May 2007

AbstractA common statistical method for assessing bioequivalence of two formulations of a chemical substance is the symmetric confidence interval of WESTLAKE (1972). As mentioned by WEST‐LAKE (1981) and SCHUIRMAN (1981) a more powerful method consists of two one‐sided t‐tests. An (1‐α)‐confidence interval consistent with the two one‐sided t‐tests procedure is given by [min(α, 0), max (0, b)] where [a, b] is the conventional (1–2α)‐confidence interval of the t‐test. This “central” confidence interval is always a strict subset of the symmetric confidence interval and thus has more power in proving bioequivalence. The central confidence interval has properties comparable with those of the conventional one‐sided confidence intervals.
One‐Way Classification ANOVA Model for the Mixture of Two Multivariate Normal Populations
Authors: Gupta A. K. , Kabe D. G. 
Published: May 2007

AbstractWhen a sample of size n is available from a mixture of two normal populations with different mean vectors and a common covariance matrix, SRIVASTAVA and AWAN (1982) develop one‐way ANOVA analysis for testing a certain composite linear hypothesis. They show that the error and hypothesis sum of products matrices have independent noncentral Wishart densities of rank unity each. However, they do not obtain the necessary Wilks' λ for testing the desired hypothesis. The present paper obtains the density of λ. This density is doubly noncentral multivariate beta density. The derivation is based on generalized Sverdrup's lemmas, KABE (1965), (1974).
The Relationship Between Two Statistical Tests for the Comparison of Two Exponential Distributions
Authors: Le Chap T. 
Published: May 2007

AbstractTo compare two exponential distributions with or without censoring, two different statistics are often used; one is the F test proposed by COX (1953) and the other is based on the efficient score procedure. In this paper, the relationship between these tests is investigated and it is shown that the efficient score test is a large‐sample approximation of the F test.
Simple Nonparametric Inference for Monotonic Processes
Authors: Schemper M. 
Published: May 2007

AbstractA scoring system for possibly censored monotonic processes is presented which allows to analyze such processes by means of standard parametric or nonparametric tests. In either case the analyses are invariant to monotonic transformations of time. Such analyses are of relevance whenever changes in degree of function are observed rather than the single and 100% loss of function of survival analysis. An example of gradually increasing function after particular reconstructive surgery is supplied.
Crossover Designs with Random Periods
Authors: Roebruck P. 
Published: May 2007

AbstractCrossover experiments usually are modelled with fixed treatment, carryover, and period effects while the effects of subjects are assumed to be random. In actual realisations of crossover experiments however periods are quite arbitrary intervals of time, depending on administrative affairs for instance and possibly they are even varying from subject to subject. Modelling these arbitrary periods as random effects either globally for all subjects or individually for each one seems to be more adequate than the assumption of fixed period effects. This paper is concerned with the two treatments, two periods crossover design. It is described that—in spite of the somewhat involved covariance structure—the estimators and tests developed for models with fixed period effects remain valid for models with random effects for periods provided that no treatment X period interaction exists.
Experiments with Three‐Treatment Three‐Period Crossover Design: Analysis Through the General Linear Model
Authors: Botter Denise A. , Singer Julio M. 
Published: May 2007

AbstractIn this paper we consider balanced three‐treatment three‐period crossover designs. Using a strategy similar to that applied in the analysis of split‐plot experiments we describe both the within and the between sample units models, as well as the corresponding Analysis of Variance. We illustrate these procedures with a numerical example and discuss their implementation through computer programs designed for the analysis of the general linear model.
Rate Constants and the Variation of Random Concentration Curves in a 2‐Compartment System
Authors: Helfenstein U. 
Published: May 2007

AbstractIn biology and medicine many substances and drugs enter the system not at regular time intervals but rather according to a random process. In the present article a situation is investigated where input enters a 2‐compartment system according to a Poisson process. The arising two random concentration curves y(t), one for the central and one for the peripheral compartment are discussed (shot noise).The equations for E[y(t)] and Var [y(t)] are derived. The dependence of E[y(t)] and Var [y(t)] and of the index of dispersion ID[y(t)] on the rate parameters is analysed and discussed in both compartments. The arising calculations were considerably simplified by means of “Mathematica”, a computer program which allows to perform symbolic calculations.
Concomitant Information in Competing Risk Analysis
Authors: Spivey L. B. , Gross A. J. 
Published: May 2007

AbstractA competing risk model, accommodating both Type I censoring and random withdrawals, is expanded to incorporate concomitant information by allowing the parameters of the underlying distributions to be a linear function of two covariates. The model is developed for two competing risks, one following a Weibull distribution and the other a Rayleigh distribution, and random withdrawals following a Weibull distribution. A method is developed for testing the equality of the coefficients for a given covariate for each of the competing risks using MLE'.
Rank Covariance Methods for the Analysis of Survival Data
Authors: Amini S. B. , Woolson R. F. 
Published: May 2007

AbstractA procedure for comparing survival times between several groups of patients through rank analysis of covariance was introduced by WOOLSONand LACHENBRUCH(1983). It is a modification of Quade' rank analysis of covariance procedure (1967) and can be used for the analysis of right‐censored data. In this paper, two additional modifications of Quade' original test statistic are proposed and compared to the original modification introduced by Woolson and Lachenbruch. These statistics are compared to one another and to the score test from Cox' proportional hazards model by way of a limited Monte Carlo study. One of the statistics, QR2, is recommended for general use for the rank analysis of covariance of right‐censored survivorship data.
Parametric and Parametrically Smoothed Distribution‐Free Proportional Hazard Models with Discrete Data
Authors: Sturm Roland 
Published: May 2007

AbstractThis paper discusses discrete time proportional hazard models and suggests a new class of flexible hazard functions. Explicitly modeling the discreteness of data is important since standard continuous models are biased; allowing for flexibility in the hazard estimation is desirable since strong parametric restrictions are likely to be similarly misleading. Simulation compare continuous and discrete models when data are generated by grouping and demonstrate that simple approximations recover underlying hazards well and outperform nonparametric maximum likelihood estimates in term of mean squared error.
Random Censorship, Competing Risks and a Simple Proportional Hazards Model
Authors: Rao B. Raja , Talwalker Sheela 
Published: May 2007

AbstractThe present paper discusses a health situation in which the individuals in a biomedical or an epidemiological cohort study are exposed simultaneously to several risks of death, such as cancer, heart disease, stroke, renal failure, emphysema, etc. and in which the life times of these individuals are independently censored on the right by some censoring mechanism. ARMITAGE' (1958) simple proportional hazards model is examined with respect to several probability models for the life time and censoring distributions.
A Multiraters Agreement Index for Ordinal Classification
Authors: Jolayemi E. Teju 
Published: May 2007

AbstractAn agreement index among more than two raters who employ ordinal classification is proposed here as an extension of the agreement index set up to consider such agreement between two raters as outlined by (JOLAYEMI, Biom. J. 32 (1990), 87–93). The method of application is outlined using a clinical diagnosis involving seven pathologists.
A Computer Programme Package for the Statistical Analysis of Spatial Point Processes in a Square
Authors: Koen C. 
Published: May 2007

AbstractA computer programme for the statistical analysis of point data in a square is described. Several tests for randomness of the distribution of points are possible. The most comprehensive of these are comparisons of the empirical distributions of the inter‐point and closest neighbour distances with their respective expected distributions under complete randomness, and tests based on Ripley' L function; using these, significant aggregation or regularity can be identified. It is also possible to calculate statistics of properties (“attributes”) associated with each spatial point, as well as to compare statistics for sub‐areas of the experimental square. Several measures of spatial autocorrelation are available, amongst them correlograms and variograms. The programme can also find the tesselation of the study area and correlate tile properties with the point attributes. The procedures are illustrated by references to the spatial distribution and mound heights of Trinevitermes trinervoides on a study area in South Africa. Although the programme was developed specifically for application in entomology, it could be used to analyse data from many other disciplines.