bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Covariance in Split Block Design
Authors: Kuczyński M. 
Published: May 2007

AbstractIn this paper the analysis of covariance in the split block design with many concomitant variables is presented. The problems concerning the estimation of parametric functions and testing hypotheses are discussed. In the presentation of the model three kinds of regression coefficients for individual sources of variation are taken into consideration. It is shown that for every estimable function of fixed effects, the best linear unbiased estimator under the assumed model is the same as the best linear unbiased estimator under the model with covariance matrix equal to identity matrix multiplied by a positive constant. A variance of this estimator can be calculated by the method presented here. Test functions for standard hypotheses concerning fixed effects are obtained.
Calculating Parameters of Multivariate F Distribution for Simultaneous Testing Linear Hypotheses
Authors: Dewięga T. , Graboś Z. 
Published: May 2007

AbstractFor testing a finite number of linear hypotheses the SANOVA method can be used. This method is based on the multivariate F distribution. In special case the multivariate F distribution depends on correlation coefficients of so called “accompanying” normal distribution. In this paper, formulas for calculating these coefficients are given. Some experimental designs are discussed in more detail. Theoretical considerations are illustrated by numerical examples.
A Variation of the Method of Translation to Generate Bivariate and Multivariate Survival Distributions with Competing Risk or Reliability Applications
Authors: Rao B. Raja 
Published: May 2007

AbstractIn the present paper, a variation of the methode of translation is discussed to generate bivariate or multivariate survival distributions starting a given bivariate or multivariate distribution which is not necessarily a life distribution. The new distribution has been called the dual of the given distribution. The duals of several bivariate and multivariate famílies of distributions are obtained, such as FRECHET'S, FARLIE‐GUMBEL‐MORGENSTERN'S, MARDIA'S and PLACKETT'S, among others. A necessary and sufficient condition is given for a bivariate distribution to be its own dual. Thus the present paper generates several survival distributions in addition to what are already available in the literature. These have important applications in competing risk theory or reliability of engineering systems.
A Comparison between the LEHMACHER & WALL Rank Tests and Pyhel's Permutation Test for the Analysis of r Independent Samples of Response Curves
Authors: Willmes K. 
Published: May 2007

AbstractLEHMACHER & WALL'S (1978) example of the application of a rank test for the comparison of two independent samples of response curves is reanalyzed by PYHEL'S (1980) permutation test for the hypothesis of parallelism of response curves. This permutation test is part of a complete evaluation of effects for a split‐plot design using the permutation test based procedure by WILLMES & PYHEL (1981). Differences in test decisions are discussed.
Predictive Configural Frequency Analysis Evaluated by Simultaneous Berchtold‐Corrected Fourfold X2‐Tests
Authors: Heilmann W.‐R. , Lienert G. A. 
Published: May 2007

AbstractFor testing against outlying cells in r × c contingency tables in predictive configural frequency analysis, it is suggested not to replace the usual PEARSON fourfold X2‐test by YATES' discontinuity corrected test but by BERCHTOLD'S test correcting for skewed hypergeometric distributions. In general, the BERCHTOLD correction is most efficient for tables involving three small and one large fourfold frequency. The correction is illustrated by configural frequency analysis of data from psychotherapy research.
Studies of Lognormality on Mortality Statistics
Authors: Izsák J. , Juhász‐Nagy P. 
Published: May 2007

AbstractFor the global investigation of the frequencies of the animal or plant species, special methods where worked out decades ago. The authors recommand them for the study of morbidity and mortality statistics. When studying mortality statistics of the United States, they found that the truncated lognormal distribution could be fitted well to the totality of the causes of death frequencies in a sense sketched in the paper. But the logarithmic series was not suitable for fitting.
On Significance Testing in Comparative Epidemiologic Research
Authors: Nurminen M. , Mutanen P. , Järvinen E. 
Published: May 2007

AbstractThe choice of the referent entity in comparative epidemiologic studies is, of course, crucial to the attainment of a valid and sharp contrast. A commonplace procedure in large sample significance testing for (multiple) fourfold (and extended) tables is to base the estimation of the expected value (and/or the variance) on the combined study and comparison experience. This procedure is, however, deplorable in that in interim stages of the study it may hide the underlying difference in rates. The notion that the probability of the realization of the observed number of exposed cases be evaluated unconditionally assuming a binomial model with the Bernoulli parameter estimated solely by the rate in the referent series is considered. This outlook is carried over to bilateral testing. A chi square criterion accommodating this viewpoint could be used to canvass the accrued data for deciding on the prospects of continuing the data collection. A test employing exact variance estimates is derived and various methods for computing an ‘exact’ significance probability are developed. The procedure is exemplified by artificial data and accompanied by a discussion of its applicability.
A Generalized Intrinsic Rank Test for k Independent Samples
Authors: Kannemann K. 
Published: May 2007

AbstractThe original intrinsic rank test is generalized in that the sizes of the k samples may now be arbitrary, and the number of intrinsic rank intervals need not equal the number of samples. Furthermore, the size of these intervals can be made variable, subject only to relatively mild constraints. These generalizations permit the formulation and testing of more specific hypotheses concerning the commonality of the sample distributions. A generalized intrinsic rank function is used to transform the usual ordinal ranks, obtained from the combined samples, into intrinsic ranks. Original sample identity and intrinsic ranks are then cross‐tabulated and evaluated as 2‐way contingency table.
Bivariate Modified Power Series Distribution Some Properties, Estimation and Applications
Authors: Shoukri M. M. , Consul P. C. 
Published: May 2007

AbstractThe class of bivariate modified power series probability distribution (BMPSD) has been defined by P(X = x, Y=y) =a(x, y) (g(ϑ1 ϑ2))x (h(ϑ1, ϑ2))xwhere a(x,y) is a sub‐set of the Cartesian product of the set of non‐negative integers and g(ϑ1, ϑ2), h(ϑ1 ϑ2) and f(ϑ1, (ϑ1, ϑ2) are positive finite and successively differentiable functions of ϑ1and ϑ2. It includes a very large number of well known probability distributions. The recurrence relations for central moments and factorial moments have been determined. Also, the M.L. estimators for ϑ1 and ϑ2 and their asymptotic biases and variances are obtained. Some important properties are discussed. The results of an BMPSD have been applied to derive the corresponding results for the bivariate generalized negative bino‐mial distribution and the bivariate Lagrangian Poisson distribution.
On a Simple Procedure of Inclusion Probability Proportional to Sizes (IPPS) Sampling
Authors: Kumar Pranesh , Agarwal S. K. 
Published: May 2007

AbstractA simple method of inclusion probability proportional to sizes is proposed for samples of size three units. It is shown that the variance of the HORVITZ‐THOMPSONestimator based on the proposed sampling scheme is uniformly smaller than that of the customary estimator used in the probability proportional to sizes with replacement sampling. Further, its performance over RAO‐HARTLEY‐COCHRANand SAMPFORDsampling schemes has been studied empirically for some of the natural populations.
A Note on RAO's Inclusion Probability Proportional to size Sampling Scheme
Authors: Agarwal S. K. , Kumar Pranesh 
Published: May 2007

AbstractA sufficient condition that the variance of HORVITZ‐THOMPSONestimator for RAO's (1965) inclusion probability proportional to sizes sampling scheme of selecting two units is uniformly smaller than that of RAO, HARTLEYand COCHRAN(1962) estimator has been obtained.
A Unique Genetic Distance
Authors: Gregorius H.‐R. 
Published: May 2007

AbstractThe problem of measuring distances between discrete frequency distributions is considered. Three conditions are stated, which are believed to reflect basic, intuitive requirements to be met by a distance measure of the above kind with particular reference to genetic frequency distributions. These conditions chiefly concern aspects of maximum distance and linearity. It is shown that exactly one function meets the conditions, and this function, having all properties of a metric, is explicitly given.
On the Best Test for Non‐Additivity
Authors: Onukogu Ike B. 
Published: May 2007

AbstractThe paper introduces the concept of confounded hypotheses. In particular, it is shown that the test of goodness‐of‐fit is confounded with the test of no interaction in a two‐way classification with one observation per cell. Further, the multiple correlation coefficient is shown to be a good criterion for choosing the best from a class of good tests for non‐additivity. Finally, the question is posed about whether different statistically adequate models do converge in some sense to the same or related mathematical functions.
Testing against Ordered Alternatives in One‐way Layout
Authors: Rao K. S. Madhava , Gore A. P. 
Published: May 2007

AbstractIn this paper we investigate a simple method of modifying well known nonparametric tests for the several samples location problem to yield a class of test statistics suitable for ordered alternatives. Optimum member of the class is identified in each case and its efficacy obtained. The method is applied to five statistics.
Maximum Likelihood Estimation of Exponential Polynomial Rate for Poisson Data
Authors: Mathers C. D. 
Published: May 2007

AbstractThe heterogeneous Poisson process with discretized exponential quadratic rate function is considered. Maximum likelihood estimates of the parameters of the rate function are derived for the case when the data consists of numbers of occurrences in consecutive equal time periods. A likelihood ratio test of the null hypothesis of exponential quadratic rate is presented. Its power against exponential linear rate functions is estimated using Monte Carlo simulation. The maximum likelihood method is compared with a log‐linear least squares techniques. An application of the technique to the analysis of mortality rates due to congenital malformations is presented.
Improved Generalized Ratio‐Cum‐Product Estimation
Authors: Singh R. Karan , Singh Gurdeep 
Published: May 2007

AbstractIn this paper, a generalized ratio‐cum‐product estimator for estimating the ratio (product) of two population means using auxiliary information on two other variables is given of which the estimators by SINGH (1969) and SHAH and SHAH (1978) are particular cases. The estimator is regeneralized when the covariance between two auxiliary variables is known.
Some Theoretical Aspects of Analysis in Half Diallel
Authors: Singh M. , Singh R. K. 
Published: May 2007

AbstractThe analysis of F1 and F2 half diallel has been discussed as compared to full diallel without reciprocal effects given by MATHER and JINKS (1971). In practice, mostly the half diallel (one‐way) crosses are prepared and erroreously analysed using the least square estimates of full diallel without reciprocal effects. The H1 and H2, however, appeared to be over estimated when full diallel without reciprocal effects estimates were used in place of those of half diallel. Least square estimates were also obtained assuming heterogeneity of error components between parents and F1/F2 families.
Statistical Significance of Mutation Frequencies, and the Power of Statistical Testing, Using the Poisson Distribution
Authors: Zar Jerrold H. 
Published: May 2007

AbstractThe Poisson distribution may be employed to test whether mutation frequencies differ from control frequencies. This paper describes how this testing procedure may be used for either one‐tailed or two‐tailed hypotheses. It is also shown how the power of the statistical test can be calculated, the power being the probability of correctly concluding the null hypothesis to be false.
Two New Discrete Distributions
Authors: Gupta Devendra 
Published: May 2007

AbstractCONSUL and JAIN (1973a) introduced a generalized Poisson distribution, which has applications in reliability theory and many biometric studies, and described some of its properties. Here we obtain two new distributions treating two of the parameters of the above distribution as random variables having gamma and absolute value distributions. One of the new distributions is related to the negative binomial distribution. Their moments also have been obtained.
Admissible Regions in a Simplex of Identity Coefficients
Authors: Karigl G. 
Published: May 2007

AbstractGenealogical relationships between any number of individuals are characterized, from the genetic point of view, by the probabilitiea of ell poeeible gene identity states occuning at an autosomel locus. However, only a eubepece of the apace of all probabilities ie in fact accemible to any relationehip. Badon a theorem of THOMPSON (1076). a characterization of the admissible region in the simplex of all condeneed identity coefficients of two non‐inbred individuals is presented. Further s similar result in the caae of detailed coefficients is given.
Competing Risk Analysis for Life Table Data with known Observation Times
Authors: Yeh C. , Le C. , McHugh R. 
Published: May 2007

AbstractSeveral models have been proposed for the analysis of cohort mortality in the presence of competing risks (a recent account is given by ELANDT‐ JOHNSON and JOHNSON, 1980, Chapter 12).This paper describes a maximum likelihood approach to the analysis of followup data in life table format for the case of two competing risks—a specific cause and its competing complement. The model developed uses a robust survivorship assumption — the piecewise exponential — and takes into account information on time to death and time to withdrawal.
Un Point de Depart pour les Methodes Iteratives de Regression. Application a la Regression Lineaire Robuste
Authors: Dolla A. , de Beauville J. P. Asselin 
Published: May 2007

AbstractThe importance of the starting point for iterative robust regression is well known since the ordinary least square solution often used doesn't always give good results.We suggest a new method called “regression by the sectors” (RPS) as a starting point to an iterative windsorisation of the original data (ITER).We used artificial samples to compare RPS and other quick techniques of fit: regression by median, Hinich‐Talwar's method, L1 norm minimization. Besides RPS‐ITER algorithm is tested (examples and simulations) in relation to algorithms using different starting points associated to ITER.The results show the superiority of RPS‐ITER.
Comparison of Populations Based on Attribute Data, when Covariance Matrices are Unequal
Authors: Misra R. K. 
Published: May 2007

AbstractMahalanobis—like distance indices B2 and G2 of BALAKRISHNAN and SANGHVI (1968) are employed to compare multinomial populations of proportions in human data. Recently, BOWERING and MISRA (1982) employed these methods, with modifications, in a different field viz. to compare fish stocks, based on meristic characters. The method of BALAKRISHNAN and SANGHVI (1968), however, assumes equality of covariance matrices, which is doubtful with multinomial populations of proportions. In this paper a statistical method for comparing such populations (where covariance matrices are not equal) is presented. Also, a feature of the G2 method of BALAKRISHNAN and SANGHVI (1968) is discussed, which makes its statistical status a little more clear.
Randomness and Order in a Forest with Trees in Rows‐a Case Study
Authors: Stoyan D. , Ohser J. 
Published: May 2007

AbstractThe correlations between intertree distances and stem volumina of trees in an artificial pine wood with trees in rows are studied. Several stochastic models are suggested, and methods of the theory of random measures are used. A method for estimating the produce of woods of the type considered is suggested.
Erweiterung des Mantel‐Haenszel‐Tests auf K(>2) Gruppen
Authors: Zimmermann H. 
Published: May 2007

AbstractThe Mantel‐Haenszel‐Test, which is widely used as the so called logrank‐test for survival data, was developed for two groups with ordinally scaled data. It is shown that it can be applied to more than two groups, and that the test statistic is easily derived from the F‐statistics of standard oneway analysis of variance procedures.
A Truncated Proportional Hazards Test
Authors: Lachenbruch P. A. , Seibert S. , Amini S. 
Published: May 2007

AbstractWe present two truncated proportional hazards tests. The first, which is applicable to those cases in which the time of action of an agent or treatment is known, was studied in two forms: One uses expected Fisher information and the other observed Fisher information. In this case the expected information statistic, C1(a0), had properties superior to the observed information statistic and is recommended. The use of the X2 distribution with one degree of freedom for percentiles appears to be satisfactory. When the time of action is unknown, a statistic based on the maximum of the C1(a) statistics is used. A simulation study gives empirical percentiles for the Max C1(a) statistic which agree with those given in a study by Muenz, Green and Byar (1977).
A generalized Friedman test for data defined by intervals
Authors: Schemper M. 
Published: May 2007

AbstractIf observations are restricted in such a way that only intervals covering the true but hidden values are known—situations found in clinical studies or analyzing laboratory data‐standard nonpara‐metric procedures fail. The present paper suggests the use of generalized Friedman tests, if the sample consists of nk observations, with one observation from each of k treatments in each of in blocks. Furthermore the proposed test enables Friedman‐type analyses of censored data. An example is given and a computer program facilitating the use of the test is introduced.
Multiple Comparisons of Polynomial Distributions
Authors: Royen Th. 
Published: May 2007

AbstractAsymptotically correct 90 and 95 percentage points are given for multiple comparisons with control and for all pair comparisons of several independent samples of equal size from polynomial distributions. Test statistics are the maxima of the X2‐statistics for single comparisons. For only two categories the asymptotic distributions of these test statistics result from DUNNETT'S many‐one tests and TUKEY'S range test (cf. MILLER, 1981).The percentage points for comparisons with control are computed from the limit distribution of the test statistic under the overall hypothesis H0. To some extent the applicability of these bounds is investigated by simulation. The bounds can also be used to improve Holm's sequentially rejective Bonferroni test procedure (cf. HOLM, 1979).The percentage points for all pair comparisons are obtained by large simulations. Especially for 3×3‐tables the limit distribution of the test statistic under H0 is derived also for samples of unequal size. Also these bounds can improve the corresponding Bonferroni‐Holm procedure.Finally from SKIDÁK's probability inequality for normal random vectors (cf. SKIDÁK, 1967) a similar inequality is derived for dependent X2‐variables applicable to simultaneous X2‐tests.
On Combination of Ratio and PPS Estimators
Authors: Pandey S. K. , Singh R. Karan 
Published: May 2007

AbstractAGARWAL and KUMAR (1980) proposed an estimator, combining ratio and pps estimators of population mean and proved that the proposed estimator would always be better (in minimum mean square error sense) than the pps estimator or the ratio estimator under pps sampling scheme for optimum value of constant k (parameter). The optimum value of k is rarely known in practice, hence the alternative is to replace k from the sample‐values. In this paper, an estimator depending on estimated optimum value of k based on sample‐values, under pps sampling scheme is proposed and studied.
Tables and Applications of the Bonferroni t‐Statistics: A Revision of Dunn's Simultaneous t‐Tests
Authors: Gottlieb R. , Lienert G. A. , Ludwig O. , Rockenfeller K. 
Published: May 2007

AbstractTables for Bonferroni‐adjusted significance levels of Student's t are provided for r = 3(1)30(5)50 etc. and alphas of 0.05, 0.01 and 0.001. The tables are suggested for various applications, for example in replacing analysis of variance of k samples by r simultaneous t tests. Use of the tables is shown by numerical examples.The adjustment of alpha for improving the efficiency of testing is made by WILKINSON for orthogonal comparisons and by HOLM for nonorthogonal comparisons.
The Matched Pairs Problem with Exponential Variates
Authors: Lachenbruch P. A. , Woolson R. F. 
Published: May 2007

AbstractTwo classes of tests for the hypothesis of bivariate symmetry are studied. For paired exponential survival times (t1j, t2j), the classes of tests are those based on t1j‐t2j and those based on log t1j–log t2j. For each class the sign, signed ranks, t and likelihood ratio tests are compared via Pitman's criterion of asymptotic relative efficiency (ARE). For tests based on t1j — t2j, it is found that: (1) the efficacy of the paired t depends on the coefficient of variation (CV) of the pair means, (2) the signed rank test has the same ARE to the sign test as for the usual location problem.For tests based on log t1j — log t2j, the ARE comparisons reduce to the well‐known results for the one‐sample location problem for samples from a logistic density. Hence, the signed rank test is asymptotically efficient. Furthermore, analyses based on log t1j — log t2j are not complicated by the underlying pairing mechanism.
Tests of Hypotheses for the General Gauss‐Markov Model
Authors: Oktaba W. 
Published: May 2007

AbstractSome theorems connected with testing the linear hypotheses in the case of the fixed general Gauss‐Markov model are given. The assumptions are as follows. Let y = Xβ + e be a fixed model where residuals ea, …, en being coordinates of the random column vector e are normally distributed with means zero and a known covariance matrix α2V non‐singular or singular and an unknown scalar parameter α2. Suppose that the known matrix X is n × p with rank r(X) = r⩽pn, where pis a number of coordinates of the unknown parameter vector β. The expected value of the random vector y with n coordinates constitutes the vector α(y) = Xβ. The formulas of the test functions (cf. theorems 2.1, 2.2, 2.3) contain c‐inverse matrices T− (defined by the condition TT−T = T), and some others when T = V + XBX′ and B = B′ is any symmetric matrix such that (cf. RAO (1971), OKTABA (1982)) r (V:X) = r (V + XBX′); (V:X) denotes matrix with two submatrices V and X.Mutual orthogonal conditions for a set of estimable parametric functions are introduced and used in the decomposition of the sum of squares for the linear hypothesis into orthogonal sums of squares each on one degree of freedom. Each of these hypotheses can be verified by the random variable F as in the analysis of variance. Some applications (cf. sections 4.1 and 4.2) of three theorems are given. Calculations without an electronic computer are rather tedious.