bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Estimation of the Segregation Parameter when Ascertainment is not Complete
Authors: Shoukri M. , Ward R. 
Published: May 2007

AbstractProcedures to estimate the genetic segregation parameter when ascertainment of families is incomplete, have previously relied on iterative computer algorithms since estimators with closed form are lacking. We now present the Minimum Variance Unbiased Estimator for the segregation parameter under any ascertainment probability. This estimator assumes a simple form when ascertainment is complete. We also present a simple estimator, akin to Li and Mantel's (1968) estimator, but without the restriction that ascertainment be complete. The performance of these estimators is compared with respect to asymptotic efficiency. We also provide tables that define the required number of families of a given size that need to be sampled to achieve a specific power for testing simple hypothesis on the segregation parameter.
The Method of Unweighted Means in Unbalanced Analysis of Variance
Authors: Knoke J. D. 
Published: May 2007

AbstractFor factorial experiments with unbalanced data the method of unweighted means is an alternate method of analysis which is computationally simpler than likelihood ratio based F‐tests. The quality of the null approximation to the F‐distribution of the statistic for the method of unweighted means and the power of this test relative to the likelihood ratio test are discussed. Recommendations are made of when in the course of data analysis the superior operating characteristics of the likelihood ratio test may not outweigh the computational simplicity of the method of unweighted means test.
Models of Independent Action for Combination Therapy
Authors: Korn E. L. 
Published: May 2007

AbstractTwo methods of applying Finney's concept of simple independent action are suggested for examining possible synergism in combination therapy. In one model the treatments act independently at one time to cure the disease. In the other model the treatments act independently continuously to prevent the disease from progressing to a terminal outcome. The implications of these models for the interaction terms of a proportional hazards model, a log‐linear model on death rates, and a logistic model are discussed.
A Model of Genome Size Dynamics During Speciation
Authors: Rodin S. N. , Berdnikov V. A. , Zharkikh A. A. 
Published: May 2007

AbstractA model developed for the evolving size of the repetitive part of the eukaryote genome during speciation was subjected to analytical and computer treatment. The basic assumption of the model was that two classes of repetitive DNA contribute mainly to macroevolutionary changes in genome size: arrays of tandem repeats (ATR) changing through unequal crossover and mobile genetic elements (MGE) changing presumably through an integration mechanism of the Tn‐ and Is‐kind operating in bacteria. Within the framework of this model, the macroevolution of the MGE size is formally equivalent to that of the ATR in the particular case when shifts of chromatids have only one repeat out of register. This allowed us to consider genome size as a large set of various ATRs. The results obtained are as follows. If the duplication and deletion of repeats have unequal fixation probabilities during each speciation act, the predicted species distributions of genome size significantly deviate from the real ones; if they have equal fixation probabilities, there is a conformance between calculated and real distributions. In the latter case, the model reproduces the salient features of real distributions upon acceptance of 1) upper selective boundary nonspecifically limiting increase in genome size within the evolving taxonomic group and 2) non‐neutrality of variability in genome size with respect to speciation.
An Examination of the Conservative Nature of “Classical” Confidence Limits for a Proportion
Authors: Walters D. E. 
Published: May 2007

AbstractThe performance of the standard confidence limits for a proportion is studied over the entire range of proportions, and for various prescribed values of the nominal confidence coefficient. In the light of the conservative nature of these limits, modifications are suggested resulting in limits with average confidence coefficients close to the 95% nominal value. A comparison is made with a solution obtained from the application of Bayes's theorem to the problem.
Sequentially Rejective Test Procedures for Detecting Outlying Cells in One‐ and Two‐Sample Multinomial Experiments
Authors: Perli H.‐G. , Hommel G. , Lehmacher W. 
Published: May 2007

AbstractFor multiple testing of multinomial models in the case of one or two samples we propose using test procedures based on the principle described by MARCUS, PERITZ and GABRIEL (1976). These methods are based in each step of the sequentially rejective strategy on tests which exhaust the full α level (i.e. which are not conservative). The tests can be performed in a finite or asymptotic version.
On a Model for Hazard Rates
Authors: Paranjape Sharayu , Rajarshi M. B. , Gore A. P. 
Published: May 2007

AbstractThis note proposes a new model for summarising data on survival distribution. A simple graphical method (or equivalently a linear‐regression‐based method) for estimation of parameters is given. The model is shown to describe adequately data on Survivorship of Starling Birds reported by LACK (1943) and data on power generators reported by DHILLON (1981). A comment is added to illustrate how one can obtain a goodness of fit statistic which has a chi‐squared distributions.
A Relationship Between two Fundamental Concepts in Drug Combination Theory
Authors: Wolf Th. , Unkelbach H. D. 
Published: May 2007

AbstractTheories for the dose response analysis of drug combinations have been developed along two separate lines. In the first line, mainly followed by pharmacologists, the concept of “additivity” is of central importance. A corresponding central concept in the second line, which was mainly followed by biometricians, is that of “simple similarity”. We show that simple similarity implies additivity and we give a condition under which the reverse holds.
Analysis of Line × Tester Progenies Compared in Orthogonally Supplemented Efficiency Balanced Incomplete Block Design
Authors: Kaczmarek Z. , Kielczewska H. , Luczkiewicz T. 
Published: May 2007

AbstractAn analysis of experimental design is suggested for comparing progenies of lineXtester mating system. The line × tester mating system is an expanded top‐cross mating system, used frequently in practice. This system is of interest for breeders dealing with estimation and testing of general as well as specific combining abilities. In the suggested design, treatments, i.e. hybrids obtained in crosses, and testers are studied in orthogonally supplemented incomplete block design. Analysis of variance has been presented, estimators of expected values for progenies and for testers have been given, testing of hypotheses concerning contrasts of interest for progenies, lines and testers has been discussed. Estimators of effects of general and specific combining abilities as well as tests permitting for testing the significance of various genetic parameters, have also been given.
The Use of Combined Classifiers in Medical Functional Diagnostics
Authors: Wernecke K.‐D. , Unger S. , Kalb G. 
Published: May 2007

AbstractIn otological and ophthalmological functional diagnostics it is typical to record for a certain individual several similar biopotentials under different conditions of stimulation and/or to collect various potentials for the same individual.Since the combination of these different data collected from a patient is of interest, coupling of the classification results obtained for each single data set seems desirable.Based on sample classifiers, obtained by linear discriminance analysis, of acoustically or visually evoked potentials from selected patients an algorithm is proposed for their coupling, which logically links the various rules of allocation and is based on the principle of assignment by highest likelihood.Furthermore, the procedure may be modified by inclusion of corresponding confidence intervals for the determined allocation frequencies.The results obtained for the groups of patients investigated show a considerable improvement of classification as judged from the error rates being distinctly reduced after the coupling.
How to Use the Two Sample t‐Test
Authors: Cressie N. A. C. , Whitford H. J. 
Published: May 2007

AbstractThis work discusses how two sample t‐tests behave when applied to data that may violate the classical statistical assumptions of independence, heteroscedasticity and Gaussianity. The usual two sample t‐statistic based on a pooled variance estimate and the Welch‐Aspin statistic are treated in detail. Practical “rules‐of‐thumb” are given along with their applications to various examples so that readers will easily be able to use such tests on their own data sets.
The Effect of Categorization on a Simple Analysis of Variance Model
Authors: Rayner J. C. W. , Dodds K. G. , Best D. J. 
Published: May 2007

AbstractMany statistical procedures assume a continuous model in spite of the fact that observations are necessarily discrete. Here we consider a simple ANOVA model—one factor with fixed effects—and assess the effect of categorisation by simulating sizes and calculating asymptotic relative efficiencies. Even for severe categorisation the effects are small.
A Statistical Method for Comparison of Two Structures and Its Biological Applications
Authors: Rachman M. I. , Kozyakov S. Ja. 
Published: May 2007

AbstractSome experimental methods applied to biological investigations allow to find a number q of homogeneous discrete components that determine a structure of the object in the study and the to establish the presence of some components from these q in compositions of other n objects. Such data form a nXq incidence matrix. In this paper a statistical approach is suggested for revealing the associated components in two different structures of the object. The procedure is based on joint consideration of two sampling incidence matrices. An application of this method is demonstrated by analysis of relationships between antigens and proteins of one strain of cyanobacteria. The method may be useful in different scientific areas, e.g. psychology, when direct experimental comparison of components from two structures is difficult.
Small Sample Properties of the Likelihood Estimator in Proportional Hazard Regression Models with Omitted Variables
Authors: Brännäs K. , Pohjanpalo J. 
Published: May 2007

AbstractThe paper deals with the effects of incorrectly omitted regressor variables in a parametric proportional hazard regression model. By studying conditions for equality between the estimators of correct and incorrect models it is demonstrated analytically that such cases are not to be expected in practise. A small sample Monte Carlo experiment indicates severe negative effects on the retained parameters both in terms of bias and mean square error.
Missing Techniques in Complete Diallel Crosses
Authors: Kaushik L. S. , Puri P. D. 
Published: May 2007

AbstractThe missing of observations in agricultural field experiments is quite common due to several natural hazards and at present no method of analysis of diallel crosses exists when one or two observations are missing. Therefore, the method of combining ability analysis of diallel crosses (including parents and reciprocals) for one and two missing observations based on TOPHAM (1956) model and using BARTLETT (1937) missing plot technique has been presented in this paper. The formulae for estimating genetical parameters, calculatings um of squares due to these parameters and for calculating variances due to the estimates of parameters have been presented. A numerical example have been given for illustrating the technique.
A Note on Estimation of Population Means Having Equal Coefficient of Variation on Successive Occasions
Authors: Sisodu B. V. S. , Singh Rajendba , Izatnagab Lv. R. I. 
Published: May 2007

AbstractFollowing SEN & GERIG (1975) an estimator for the population mean on the current occasion is proposed. It has been shown that the estimator is more efficient than ‘mean per unit estimate’ for all kind of populations. The eetimatiors suggeated by SEN & GERIG (1976) and SEABM (1964) are also found to be relatively less efficient than the proposed estimator.
Sequential Analysis of Survival Times in Clinical Trials
Authors: Olschewski M. , Schumacher M. 
Published: May 2007

AbstractThis paper provides a synopsis of statistical methods which can be used for the sequential analysis of possibly censored survival times in clinical trials. Especially, results on the asymptotic behaviour of the Breslow‐Haug statistic and on the sequential version of the logrank statistic are presented in a standardized terminology. In addition, formulae for the explicit calculation of linear and square‐root boundaries for sequential plans are given and illustrated by an example. Practical problems of applying these methods when monitoring a fixed‐sample clinical trial as well as group sequential methods and calculation of P‐values are also discussed.
On the Performance of the SPRT for Correlation Coefficient: Normal and Mixtures of Normal Populations
Authors: Kocherlakota K. , Balakrishnan N. , Kocherlakota S. 
Published: May 2007

AbstractThe sequential probability ratio test (SPRT) for the correlation coefficient is examined in the normal and non‐normal situations. In the latter case, we evaluate the robustness of the normal procedure when sampling from the mixtures of normal distributions. Two models are introduced for this type of nonnormality. It is shown that in the case of moderate nonnormality, the normal procedure is robust while for extreme nonnormality, the normal procedure is not recommended.
Gram‐Schmidt Orthogonalization of Multinormal Variates: Applications in Genetics
Authors: Bonney G. E. , Kissling G. E. 
Published: May 2007

AbstractThe computation of an N‐variate normal density function requires the inversion of an N × N co‐variance matrix. Furthermore, if each mean depends on u unobservable factors, a mixture of uN N‐variate normal densities must be computed, making likelihood calculations impractical even for moderate N. The Gram‐Schmidt orthogonalization process is used to express a multinormal density as a product of univariate normal densities. When the pattern of the correlation matrix is taken into account the formulas may be considerably simplified. In some cases each of the orthogonal variates can be written as a linear combination of only a few of the original variates. Such results are crucial for applications of multinormal distributions and of mixtures of multinormal distributions. An intraclass correlation model and a genetic variance components model applicable to family data are discussed as examples.
A Simplified Newton Method for Computing the Factor Loadings in Maximum Likelihood Factor Analysis
Authors: Focke Joachim 
Published: May 2007

AbstractA simplified Newton iteration scheme for computation of factor loadings in maximum likelihood factor analysis is described. It operates in the space of factor loadings and avoids eigenvalue problems. From this, a comparatively small computational effort results. Besides of the case of positive unique variances, also the Heywood case is considered, where some unique variances vanish. The ability of the proposed method is demonstrated in three examples, results and iteration process are compared with data given in literature.
Testing for Independence of Binary Responses
Authors: Fidler V. , de Jonge A. B. 
Published: May 2007

AbstractIn the context of experiments involving visual inspection of random dot patterns the problem of testing the null hypothesis of independence of binary responses is considered. A flexible model for dependence between binary responses is proposed. Two tests, optimal under different versions of the model, are derived. These two tests turn out to involve the same computations as the Wilcoxon two sample test and the runs test respectively.
Variance Calculations for Direct Adjusted Survival Curves, with Applications to Testing for No Treatment Effect
Authors: Gail M. H. , Byar D. P. 
Published: May 2007

AbstractSeveral investigators have recently constructed survival curves adjusted for imbalances in prognostic factors by a method which we call direct adjustment. We present methods for calculating variances of these direct adjusted survival curves and their differences. Estimates of the adjusted curves, their variances, and the variances of their differences are compared for non‐parametric (Kaplan‐Meier), semi‐parametric (Cox) and parametric (Weibull) models applied to censored exponential data. Semi‐parametric proportional hazards models were nearly fully efficient for estimating differences in adjusted curves, but parametric estimates of individual adjusted curves may be substantially more precise. Standardized differences between direct adjusted survival curves may be used to test the null hypothesis of no treatment effect. This procedure may prove especially useful when the proportional hazards assumption is questionable.
Estimation of Heritability for Samples from Non‐Normal Situations
Authors: Singhal R. A. , Jain J. P. 
Published: May 2007

AbstractMathematical expressions, to investigate the effects of mederate departure from normality assumption on the point estimate and on the probability of getting a negative estimate of genetic heritability, in a balanced situation, have been derived. The numerical results show that the point estimate is over sensitive whereas the probability of a negative estimate is insensitive to this violation.
Two‐Stage Least Squares Analysis of Hierarchical Linear Models
Authors: Onukogu I. B. 
Published: May 2007

AbstractThis paper has two major objectives. The first is to present a two‐stage least squares procedure for estimation of the parameters in a linear model whose parameters are in themselves linear functions of some hyperparameters. The second, and perhaps more important point, is that the new estimator can be shown to be generally more precise than either the Bayesian or the generalized single‐stage least squares estimator reported by LINDLEY and SMITH (1072).
The Asymptotic Covariance Matrix of the Maximum Likelihood Parameter Estimator in Conditional Poisson Log‐linear Models
Authors: Bonett D. G. , Bentler P. M. , Woodward J. A. 
Published: May 2007

AbstractThe asymptotic covariance matrix of the maximum likelihood estimator for the log‐linear model is given for a general class of conditional Poisson distributions which include the unconditional Poisson, multinomial and product‐multinomial, as special cases. The general conditions are given under which the maximum likelihood covariance matrix is equal to the covariance matrix of an equivalent closed‐form weighted least squares estimator.
Some Monte Carlo Studies on the Comparison of Several Means Under Heteroscedasticity and Robustness with Respect to Departure from Normality
Authors: Tan W. Y. , Tabatabai M. A. 
Published: May 2007

AbstractBy using Monte Carlo studies, this paper compares the Welch test, the James test and the Brown‐Forsythe test for comparing several means under heteroscedasticity. It appears that all the tests are quite robust with respect to departure from normality. The Brown‐Forsythe test is at least as good as the James test and the Welch test; but the differences are so small that the choice is immaterial for practical purposes.
A Two‐stage Procedure with Controlled Error Probabilities for Testing Bioequivalence
Authors: Srinivasan R. , Langenberg P. 
Published: May 2007

AbstractThe procedures currently used for testing the bioequivalence of two drug formulations achieve control over the error probability of erroneously accepting bioequivalence or over the probability of erroneous rejection, but not over both error probabilities. A two‐stage procedure that rectifies this drawback is presented, assuming that the performance of the drug is characterized by a normally distributed variate.
Variances and Asymptotic Distributions of Direct Standardized Rates
Authors: Cohen Arthur , Davis Linda J. 
Published: May 2007

AbstractFormulas for the variance of direct standardized rates are given for three different sampling models. The three models are product multinomial models when population totals are fixed by design, or strata totals are fixed by design, or cell (each population—each stratum) totals are fixed by design. Asymptotic distributions are derived for each model. A discussion on the relevance and use of standardized rates and the need for distribution theory is also provided.
Inference Based on Ranks with Tied Failure Time or Grouped Survival Data
Authors: Pettitt A. N. 
Published: May 2007

AbstractScores for the analysis of distinct failure time data using ranks are modified to deal with tied failure times or grouped data. Approximate techniques for inference for regression parameters are considered for ‘proportional odds’ and ‘proportional hazards’ survival data involving tied failures or grouped data. An illustration is given involving a two sample problem.
Alternatives to the Chi‐Square Test of Homogeneity in 2×2 Tables and to Fisher's Exact Test
Authors: Sachs L. 
Published: May 2007

AbstractIn comparing two independent binomial proportions by modified X2tests: Gart's modified likelihood‐ratio, Overall and Starbuck's “tailoredF”, Pearson's adjustedX2[=X2multiplied by (n‐ 1)/n] and its skewness‐corrected version proposed by Berchtold, it was found that the last two have error probabilities that in the mean are close to the significance level.
On Relative Precision in Stratified Sampling for a Mean with Fixed Cost
Authors: Bennett B. M. , Islam M. A. 
Published: May 2007

AbstractThis paper considers the extrema of the relative precision (R. P.), or the ratio of the variance of optimum allocation to that of proportional allocation in stratified sampling for a mean (=Y) or total (=Y) when there is a fixed cost C=co+σnhch over L strata. The upper bound of R. P. is shown to be equal to unity, though the lower bound can be negative while approaching zero if the finite population size N→∞. Numerical results (cf. Table) when the upper bound of R. P. = 1 is attained are included for the cases L≦4 with various combinations of {Wh}, {ch} and a fixed cost C; these give the appropriate sample sizes (=np) determined for proportional sampling in the cases of finite populations of sizes N=5000, 10,000 respectively.
On Analysis of Covariance Under Heteroscedasticity and Robustness with Respect to Departure from Normality
Authors: Tan W. Y. 
Published: May 2007

AbstractIn this paper we consider a covariance model under heteroscedastic variances and propose a procedure for testing treatment effects. A simultaneous procedure for comparing the treatment effects is also developed. Some Monte Carlo studies indicate that the effects of departure from normality may not be very serious although some effects do exist due to high level of heteroscedasticity.
The Doubly Noncentral Distribution of Wilks' Statistic in MANOVA
Authors: Gill D. S. , Siotani Minoru 
Published: May 2007

AbstractWhen plot effects are modeled in a randomized block design in multivariate analysis of variance the error and hypothesis matrices have independent noncentral Wishart distributions. This gives rise to doubly noncentral distribution of Wilks' statistic. The doubly noncentral distribution of Wilks' statistics, when the noncentrality matrices for the noncentral Wishart distributions in the above setting are of rank one or two, is investigated.