Analysis of covariance in mixed models with unequal subclass numbers

Blue of estimable linear functions and exact tests of hypotheses concerning such functions usually do not exist in the covariance model with random factors having unknown variances. This is true even in the equal subclass numbers case. This paper suggests alternative methods for finding linear unbiased estimators and presents methods for computing sampling variances which are linear functions of the unknown parameter variances. Also, higher level covariates are defined and nonestimability problems resulting from association of such covariates with fixed factors are discussed.     

Lagrange Multiplier Tests for Normality Against Seminonparametric Alternatives

In this article, I derive the Lagrange multiplier test of the null hypothesis that a stationary random vector has a (possibly heteroscedastic) normal distribution against the alternative that the distribution is a member of the family with seminonparametric probability density functions considered by Gallant and Tauchen (1989). The test is shown to contain special cases of the moment tests proposed by Newey (1985) and Tauchen (1985). Evidence from a small simulation study is reported, showing that the test has reasonable finite-sample properties in moderately sized samples. The test is applied to the change of price in a treasury-bill data series analyzed by Tauchen and Pitts (1983) and Tauchen (1985).     

On the distributions of the differences between the estimated autocorrelations and partial autocorrelations at the same lag

Pukkila (1982) introduced a new portmanteau-type test of white noise. The test is based on the differences between the estimated autocorrelations and the corresponding partial autocorrelations. In the present paper the distributions of these differences are consider in the case of normal white noise. Approximations to these distributions are given. Goodness of fit of these theoretical distributions and the corresponding observed distributions is studied using simulated time series of various lengths.     

Almost most powerful tests against composite alternatives

Likelihood ratio considerations are used to derive uniform bounds on the acceptance and rejection regions of the family of locally most powerful randomization tests for a two-sample comparison of censored data, When applied to radioimmunoassay data, these bounds are close enough to permit effective decision making. The methodology extends to a wide class of testing problems.     

Multiplicity: discussion points from the Statisticians in the Pharmaceutical Industry multiplicity expert group

In May 2012, the Committee of Health and Medicinal Products issued a concept paper on the need to review the points to consider document on multiplicity issues in clinical trials. In preparation for the release of the updated guidance document, Statisticians in the Pharmaceutical Industry held a one‐day expert group meeting in January 2013. Topics debated included multiplicity and the drug development process, the usefulness and limitations of newly developed strategies to deal with multiplicity, multiplicity issues arising from interim decisions and multiregional development, and the need for simultaneous confidence intervals (CIs) corresponding to multiple test procedures. A clear message from the meeting was that multiplicity adjustments need to be considered when the intention is to make a formal statement about efficacy or safety based on hypothesis tests. Statisticians have a key role when designing studies to assess what adjustment really means in the context of the research being conducted. More thought during the planning phase needs to be given to multiplicity adjustments for secondary endpoints given these are increasing in importance in differentiating products in the market place. No consensus was reached on the role of simultaneous CIs in the context of superiority trials. It was argued that unadjusted intervals should be employed as the primary purpose of the intervals is estimation, while the purpose of hypothesis testing is to formally establish an effect. The opposing view was that CIs should correspond to the test decision whenever possible. Copyright © 2013 John Wiley & Sons, Ltd.     

Testing Goodness of Fit of Parametric AFT and PH Models with Residuals

In this article, we consider the problems of testing the goodness of fit of the parametric accelerated failure time model and the Cox proportional hazards model. We consider omnibus test statistics based on residuals. The statistical distributions of Kolmogorov, Cramer-von Mises–Smirnov, and Anderson–Darling statistics are all investigated by means of Monte Carlo simulations. Type-I, Type-II, and independent random censoring situations are all considered in this study. A Monte Carlo power study has also been carried out for these tests to distinguish between various baseline models, which reveals that the Anderson–Darling test performs better than the others.     

Grouping Tests for Misspecification: An Application to Housing Demand

We consider several grouping tests for regression misspecification, with reference to housing-demand function estimation. We compare three existing test procedures, demonstrate modifications necessary in most applications, and propose a fourth test to distinguish between two categories of potential specification error. The test procedures are evaluated in artificial simulations of alternative errors. Finally, we apply the tests to FHA home purchase data. We reject the hypothesis that household and grouped regressions differ only by sampling error or random mismeasurement of household income or price. Our results have implications for choices among test procedures and interpretations of previous housing-demand analysis.     

Comparisons of the asymptotic efficiencies of two sample tests for discrete distributions

The asymptotic efficiencies are computed for several popular two sample rank tests when the underlying distributions are Poisson, binomial, discrete uniform, and negative binomial The rank tests examined include the Mann-Whitney test, the van der Waerden test, and the median test. Three methods for handling ties are discussed and compared. The computed asymptotic efficiencies apply also to the k-sample extensions of the above tests, such as the Kruskal-Wallis test, etc.     

Sampling distributions of kruskal's measure of stress for an asymmetric matrix

In the past ten years multidimensional scaling of nonmetric data has been widely applied in behavioral and business research. This paper investigates the asymmetric data matrix and develops stress distributions based upon a null hypothesis of equal like­lihood in the ranking of a set of proximities.     

Zur verknüpfung von “zeitbereichsanlalyse” und “frequenzbereichsanalyse” bei saisonbereinigungsverfahren-ein beitrag zur zeitreihenanaiyse

It is charaateristic feature of the serasonal adjusment procedures generally used today that their theoretical basis consists of analyses both in the time – and frequency – domain. However, both methods of analysis are unconnected hitherto. In addition, even the modern statistical concepts considering the transfer functions of the filters used, show definitorial deficiencies, since the lengths of the lengths of the relevant frequency bands are not determined objectively. Therefore in the following paper the problems of a possible connection of both methods of analysis and a solution of the aforementioned definitorial problems by using concepts of statistical estimation theory is analyzed.