bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rank Analysis of Block Designs Having Different Cell Frequencies
Authors: Rai S. C. 
Published: May 2007

AbstractA distribution–free test is considered for testing the treatment effects in block designs with different cell frequencies. A test statistic which is a function of treatment ranks has been proposed which is distributed as chi‐square for large samples. The null distribution of the test statistic has been obtained. The entire procedure has been explained by a numerical example.
A Linear Model with Plot Effects
Authors: Gill D. S. , Janardan K. G. 
Published: May 2007

AbstractIt is a common practice to analyze the data from agricultural experiments using randomized block design where each block has homogeneous experimental units (plots). However, many times, during the period of study, due to unavoidable circumstances such as natural calamities, say floods, for example, plots are no longer homogeneous. Thus, it is desirable to consider the plot effects also in the model. An appropriate model and an example of the analysis of data with plot effects is provided here.
Analysis of Proportions in One‐ or Two‐Way Tables with Spoiled Data
Authors: Bennett B. M. 
Published: May 2007

AbstractThis paper discusses the analysis of data on proportions in contingency tables. The X2 ‘index of dispersion test’ (e.g. Fisher, 1954) is developed in these situations and compared with the use of the ‘logit’ transformation. An example using Osborn's (1979) data is given, illustrating the estimation of one or more missing observations.
Some Tests for k£2 Upper Outliers in an Exponential Sample
Authors: Likeš J. 
Published: May 2007

AbstractThe sequential procedure for testing up to k upper outliers proposed by Kimber (1982) for one‐parameter exponential distribution is modified to a two‐parameter exponential distribution. Further null distributions of some test statistics for an upper outlier‐pair in a complete or censored sample from a two‐parameter exponential distribution are given. Percentage points of the statistic T1 are tabulated.
Relative Efficiencies of a Class of Goodness of Fit Tests for Randomly Censored Data
Authors: Koziol J. A. 
Published: May 2007

AbstractWe investigate the relative performances of a class of goodness of fit procedures for randomly censored data. For purposes of planning experiments, we quantify the loss of information induced by censorship. We evaluate efficiencies against particular alternatives of interest in survival studies, as the amount of censorship increases. We caution against attributing various power and efficiency properties of the goodness of fit criteria that are obtained under no censorship to situations where the censorship is far from negligible.
Prediction of the Standardized Risk Ratio via Proportional Mortality Analysis
Authors: Marsh G. M. , Winwood J. P. , Rao B. R. 
Published: May 2007

AbstractThe relationship between the commonly used indiréctly standardized comparative mortality indices, the standardized mortality ratio (SMR) and the standardized proportional mortality ratio (SPMR) is well known; whereas, the relationship between their less commonly used directly adjusted counterparts, the standardized risk ratio (SRR) and the recently proposed externally standardized proportional mortality ratio (SePMR) has been heretofore not developed. This paper fills this void by demonstrating the algebraic and statistical relationship between the SRR and the SePMR and showing how, under some modest assumptions, valid inferences about the SRR can be based on analysis of SePMR's. More specifically, an asymptotic prediction interval has been developed for the SePMRi which, with high probability, contains the ratio RSRRi = SRRi/SRR. The utility of the SePMRi is supported empirically using data from a recent retrospective cohort study of mineral fiber workers.
Multivariate Probability in Terms of Marginal Probability and Correlation Coefficient
Authors: Seneta E. 
Published: May 2007

AbstractThis paper is motivated by a practical problem relating to student performance in a number of subjects of equal standing. Its mathematical formulation is to find an approximation to a multivariate probability of the form Pr {X1⩾a, X2⩾a, …, XN⩾a} for arbitrary a and N, in terms of p = Pr {X1⩾a} and q = Corr (Xi, Xj), i≠j, where Xi, i = 1, …, N are exchangeable random variables with mean 0 and variance unity.
Measures of Imbalance for Unbalanced Models
Authors: Khuri A. I. 
Published: May 2007

AbstractIn this paper we present a procedure to measure the degree of imbalance of an unbalanced data set. The procedure is based on choosing an appropriate loglinear model for the subclass frequencies of the data. A measure of imbalance is then introduced as some function of the chi‐squared statistic used in the goodness‐of‐fit test for the loglinear model. The proposed procedure can also be used to measure departures from certain types of balance, such as proportionality of subclass frequencies, partial balance, and last‐stage uniformity.
A Theoretical Model for Estimating Linkage in F2 Populations with Distorted Single Gene Segregation
Authors: Heun M. , Gregorius H.‐R. 
Published: May 2007

AbstractA model is presented which allows estimation of linkage from dihybrid F2 populations with distorted single gene segregation by applying the maximum‐likelihood method.For different selection processes operating on one locus at either the gametic or the zygotic level, it can be demonstrated that, if the deficit is previously taken into account, testing for free recombination can be carried out without prior knowledge of the causes of this deficit. In the presence of linkage, the expected frequencies of two phenotypic classes depend on whether gametic or zygotic selection is operating. The remaining two classes can be utilized for the estimation of linkage as their frequency ratio is independent of these selection types.The application of this procedure to situations with coupling, incomplete penetrance, gametic and zygotic selection is discussed.
Tests for Trends in Incidence Rate Ratios
Authors: Nurminen M. 
Published: May 2007

AbstractBreslow (1984) described an efficient score test for trend in incidence density rate ratios for cohort studies under a conditional Poisson or binomial model employing maximum likelihood estimation of the rate parameters. In this communication, an alternative derivation of this statistic that is based on an unconditional approach is provided, along with an examination of associated goodness‐of‐fit tests and methods of confidence interval estimation. The procedures are illustrated by a cohort study of ischemic heart disease mortality following industrial exposure to carbon disulfide.
Test Based on Independent, but Non‐identically Distributed Random Variables
Authors: Hüsler Jürg 
Published: May 2007

AbstractThe binomial test is applied for the problem of testing a hypothesis based on a sample of independent, but non‐identically distributed random variables. The used basic idea is that each random variable indicates the presence of the hypothesis. Hence each random variable is transformed such that the binomial test can be used as a simple procedure.
Multi‐Sample Slippage Test for Ordered Observations
Authors: Rai S. C. 
Published: May 2007

AbstractA multi‐sample slippage test based on ordered observations has been given. The test statistic is based on the sum of ranks of the sample. The probability distribution of the test statistic has been worked out for small sample and it turns out to be chi‐square distribution for large sample. The analytical procedure has been explained by a numerical example.
Simultaneous Selection of Extreme Populations: A Subset Selection Approach
Authors: Mishra Satya N. , Dudewicz Edward J. 
Published: May 2007

AbstractThe problem of selecting a “best” (largest mean, or smallest mean) population from a collection of k independent populations was formulated and solved by Bechhofer (1954). Gupta (1965) solved another important problem, that of selecting a subset of populations containing the “best” population from the original collection of populations. Since then many variations of the problem have been considered. Tong (1969) and Lewis (1980) have investigated the problem of selecting extreme populations (populations with a largest, and populations with a smallest, mean) with respect to one and two standard populations, respectively. In this paper we study the selection of extreme populations in absence of any standard population. We formulate subset‐selection procedures when variances are known and equal, and also in the most general case when they are unknown and unequal. Nonexistence of a single‐stage procedure is noted for this latter case (even if variances are equal). A two‐stage procedure and some of its associated properties are discussed. Tables needed for application are provided, as is a worked example.
On a Model for Estimating the Parameter of the Human Reproductive Process
Authors: Biswas S. , Sehgal V. K. 
Published: May 2007

AbstractAttempt has been made in this paper to estimate certain parameters (data pertaining to which are either not available or easily reportable) of the human reproductive process as the period of postpartum ammenorrhoea (P.P.A.), number of foetal wastages in between live births etc., using a truncated negative binomial probability model. In view of the hypothesis that the probability of foetal wastages varies from mother to mother, the truncated negative binomial distribution has been compounded by weighing with the best prior Beta distribution of the parameter. Estimation has been made by successive approximation using the method of moments.
A Method of Fuzzy‐Theory‐Based Computer‐Aided Exploratory Data Analysis
Authors: Bandemer H. , Roth K. 
Published: May 2007

AbstractWhen evaluating functional relationships from given data in an exploratory state of investigation, we only want to get an imagination of a possibly existing trend. Usually, methods of local or empirical regression are chosen to meet this purpose. In the paper we suggest an alternative using the possibilities of modern picture processing methods and computers. The data were transformed into a grey‐tone picture representing a fuzzy observation set, the maximum trace of which yieldsthedesired first impression of the trend and may serve as the starting point for further detailed evaluation of the functional relationship. The method is illustrated by a real‐data numerical example.
Dual Designs and Their Application in Genetical Experiments
Authors: Puri P. D. , Nigam A. K. , Kageyama S. 
Published: May 2007

AbstractThe dual of incomplete block designs has been studied with th́eir applications in genetical experiments. Partial diallel crosses (PDC) of type I have been constructed using balanced incomplete block (BIB) designs, partially balanced incomplete block (PBIB) designs and their dual designs. Simplified analysis of PDC has been presented using the dual property of these designs. List of optimal PDC having simple analysis has been given.
Confidence Limits on Heritability Under Non‐normal Variations
Authors: Singhal R. A. 
Published: May 2007

AbstractMoment approximation for the non‐normal sampling distribution of the ratio of mean squares in the balanced one‐way Model II is found close to that of the Snedecor's F‐distribution. The confidence limits for heritability of paternal half‐sib correlations, derived employing F‐distribution, are, in general, remarkably narrow for platykurtic and wide for leptokurtic sire effects than the normal limits. The effect of kurtosis of environmental deviations on these limits is of no consequence whereas the effect of skewness is invisible.
Statistical Analysis of Factorial Diallel Design over Environments
Authors: Wolf J. 
Published: May 2007

AbstractStarting from the experimental situation that in each of a environments all mp combinations between m maternal and p paternal genotypes are raised in b replications (blocks), a linear model is formulated for a quantitative character. On the basis of this model formulae for the analysis of variance are given. The expectations of mean squares as well as the estimations of effects (general and specific combining ability and their interaction terms with environments) and their variances are given for different combinations of fixed and random factors.
Alternative Models for Correlating Toxic Effects
Authors: Verducci J. S. 
Published: May 2007

AbstractTwo very different types of correlation are examined. First, the problem of correlating two different toxic potentials, such as mutagenesis and carcinogenesis, over a class of chemicals is discussed and shown to be quite difficult unless strong assumptions are made about the dose‐response curves for each effect. The second type of correlation is that of joint occurrences of symptoms over a population of subjects. A latent class model whose parameters are linear functions of dosage is proposed based on a two‐stage theory of carcinogenesis. This model surpasses various alternative models in predicting multiple site tumors resulting from exposure to the solvent 1,3‐butadiene.
Nonparametric Comparison of Longitudinal Response Patterns from Paired Samples Using Configural Frequency Analysis
Authors: Von Eye Alexander , Lienert Gustav A. 
Published: May 2007

AbstractNonparametric methods of Configural Frequency Analysis (CFA) for comparing longitudinal response patterns are discussed. Characteristics of diagonally symmetric frequency distributions are mapped with hypotheses on the locus of treatment effects. Test statistics for the analysis of local dependencies are discussed. In particular, applications to paired samples are considered. A biomedical example is given from research on the effects of spasmolytic drugs. Local CFA‐testing is compared with global testing. Alternative strategies of testing and the respective underlying assumptions are discussed.
Selection of Judges for Sensory Evaluation
Authors: Rai S. C. 
Published: May 2007

AbstractA test based on ordered observations for selection of consistent judges for sensory evaluation has been given. The test–statistic depends on the sum of ranks of different products under consideration. The probability distribution of the test‐statistic has been worked out for small sample and it turns out to be chi‐square distribution for large sample. The analytical procedure has been explained by a numerical example of a taste‐testing experiment.
Classical Analysis of Variance Methods and Nonparametric Counterparts
Authors: Van Der Laan Paul , Verdooren L. Rob 
Published: May 2007

AbstractThe present investigation is concerned with the use of classical and nonparametric techniques in the analysis of experiments. Occasionally biometricians are confronted with results arising from an experiment with data which do not necessarily satisfy the assumption of Normality, the basis of the classical analysis of variance methods. Sometimes the biometrician handles such a situation by transformation of the observations and applying the classical techniques. Although this attack may lead to a satisfactory analysis, the results may be questionable in a number of cases. In analyzing continuous data without the Normality assumption nonparametric methods provide realistic alternatives. In this paper a number of problems will be discussed with and without the Normality assumption resulting in the well‐known classical analysis and its nonparametric counterparts. Most of the nonparametric procedures to be discussed are based on ranks.
Analysis of Square Contingency Tables with Ordered Categories by a New Method of Applying the 1‐Weight Modified Marginal Homogeneity Models
Authors: Tomizawa Sadao 
Published: May 2007

AbstractFor square contingency tables with ordered categories, this note proposes a new method of applying Tomizawa's (1987) 1‐weight modified marginal homogeneity models and applies to the 4×4 tables on unaided vision analysed by Tomizawa (1987) and by Stuart (1955). A possible explanation which is derived from fitting those models is first obtained using this new method.
Some Results on Error Rates for Quadratic Discrimination with Known Population Parameters
Authors: Young Dean M. , Turner Danny W. , Marco Virgil R. 
Published: May 2007

AbstractLet population Πi, i = 1,2, be characterized by a multivariate normal density function, N(μi,∑i), i = 1, 2, respectively. This paper provides conditions under which simple conditional error rates may be computed for the quadratic discriminant function with known population parameters. Also, a simple bound on the overall error rate is derived. Examples are given which demonstrate the proposed methods.
Application of Logistic Regression and Logistic Discrimination in Medical Decision Making
Authors: Dietz E. 
Published: May 2007

AbstractThe logit linear model has been shown to be very useful for investigations in many fields of biology and medicine. One kind of application of this model is that of logistic discriminant analysis. To conquer some theoretical disadvantages of logistic discriminant analysis and Fisher's linear discriminant analysis too, it has been recommended to augment their model equations with appropriate interaction terms. The present paper discusses experiences with epidemiologic data going this way.
A Generalization of the GMANOVA‐Model
Authors: Hecker H. 
Published: May 2007

AbstractIt is shown that in some experimental designs the MANOVA‐ and the GMANOVA‐model are too restrictive either to yield all hypothesis tests of interest or to reflect all known features of the design. An extension of these models is derived by relating the response vectors with the unknown model parameters by linear equations which may be completely different for each of the p components of the response vector and for each of the n independent vectors. For situations, in which a Wishart‐distributed estimator for the underlying common covariance matrix is attainable, a test for any s‐dimensional linear hypothesis on the model parameters is derived.
Testing Hypotheses on the Mean Vector Under an Intraclass Correlation Structure
Authors: Bhoj Dinesh S. 
Published: May 2007

AbstractA statistic is proposed for testing hypotheses on the mean vector of a p‐variate normal distribution when the variance covariance matrix has an intraclass correlation structure. The powers of the test are computed and compared with those obtained from the statistics of Cox and Han (1982) and Clement et al. (1981). The power comparisons support the use of the proposed test.
Statistical Methods for Using Nonlinear Models to Compare Silage Treatments
Authors: Hinds M. A. , Milliken G. A. 
Published: May 2007

AbstractStatistical methods are described which can be used to compare treatments where the response is described by a nonlinear model. The nonlinear analysis of covariance is described for a one‐way treatment structure and a two‐way treatment structure. Methods for constructing confidence bands about a model and about the difference of two models are described. Examples involving the dynamics of silage fermentation are used to demonstrate the methods.
On a Mixed‐Type Randomized Rule for Selecting Superior Binomial Models
Authors: Huang Wen‐Tao , Saleh A. K. Md. Ehsanes 
Published: May 2007

AbstractWe propose a new class of selection rules for selecting superior models from finite Binomial models. This new class of rules extends the classes of classical rules and shows its superiority to the classical selection rules by some Monte Carlo results. This new class of rules is easier and more flexible to apply than these known classical rules.
A Rapid and Efficient Estimation Procedure for the Negative Binomial Distribution
Authors: Kemp A. W. , Kemp C. D. 
Published: May 2007

AbstractThis paper presents a new noniterative procedure for estimating the parameters of a negative binomial distribution. The procedure uses the first moment equation and an equation based on the weighted sample mean, with weights ωx∝ αz. The selection of a value for α is examined. A simulation study has been carried out and also the method has been applied to the 35 data sets analysed by Martin and Katti (1965, Biometrics) in order to compare it with the method of moments and with the method of maximum likelihood (ML). We conclude that the new procedure has greater relative efficiency than the method of moments; it gives estimates which are consistently close to ML and are easy to calculate.
Non‐Parametric Methods for the 2‐Period‐Cross‐Over Design Under Weak Model Assumptions
Authors: Brunner E. , Neumann N. 
Published: May 2007

AbstractA nonparametric analysis for the two period cross‐over design has first been suggested by Koch (1972) and has been discussed by Hills and Armitage (1979). As known rank tests on sums or differences of the data are applied in this procedure, the results on the one hand are not invariant under monotonous transformations and on the other hand the procedure is only correct for models with additive effects. Therefore, in the present article generalized effects will first be defined in the 2‐period cross‐over design without the assumption of a linear model and then rank test will be presented which test tese effects without the need of sums or differences of the data. In the appendix the equivalence of the hypothesis for the generalized effects to the known hypotheses for the effects in the linear model will be shown. The application of the procedures will be demonstrated by means of an example in literature.
Investigations on the Similarity of the Structure of Two Covariance Matrices for Some Blood Pressure Data
Authors: Bartkowiak A. 
Published: May 2007

AbstractWe have two sample covariance matrices of size p × p, where p is the number of variables denoting measurements of arterial blood pressure recorded in various positions and methods for women and men. The hypothesis on equality of the two covariance matrices was rejected and we want to find, why this happened and in which covariances the two matrices differ.In § 2 we explore the primary (observed) data looking for outliers and deviations from normality. We do it by drawing χ2 plots.In § 3 we look for common principal components. We use here Flury's method. We find that the data for blood pressure systolic might have a common principal axes system (P≈︁0.0866), while for blood pressure diastolic this is dubious (p≈︁0.0112). The variances of the first principal component found for woman are a little larger than those for men, and this fact explains the rejection of the classical test ∑1 = ∑2 on the equality of the two covariance matrices.After applying a common rotation to the two covariance matrices we reduce them to a nearly diagonal form. Looking at the non diagonal elements we see which covariances do not fit into the model.In § 4 we repeat the calculations from § 3 for covariance matrices calculated from the same data using robust methods.
Nearest Neighbor Classification Rule for Mixtures of Discrete and Continuous Random Variables
Authors: Wojciechowski T. J. 
Published: May 2007

AbstractIn this paper very simple nonparametric classification rule for mixtures of discrete and continuous random variables is described. It is based on the method of nearest neighbor proposed by Cover and Hart (1967). The bounds on the limit of the nearest neighbor rule risks are given. Both lower and upper bound depend on the Bayes risk and the loss function. Finally the method is compared with other existing methods on some practical data set.
Statistical Analysis of Spatial Point Processes: A Soft‐Core Model and Cross‐Correlations of Marks
Authors: Stoyan D. 
Published: May 2007

AbstractThis paper suggests correlation characteristics for marked point processes with two marks for each point and describes statistical methods for their estimation. Its use is demonstrated by means of an example, where the points are locations of pine saplings, and the marks are their heights and ages. Furthermore, a soft‐core point process model is presented. It is shown that a pattern of sites of beadlet anemones on a rock has a pair‐correlation function and intensity which can be very well approximated by the model.