Sequential Analysis of Survival Times in Clinical Trials

This 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.     

Impact of molecular biology on the detection of foodborne pathogens

Molecular biological methods that use antibodies and nucleic acids to detect specific foodborne bacterial pathogens were scarcely known a decade and a half ago. Few scientists could have predicted that these tools of basic research would come to dominate the field of food diagnostics. Today, a large number of cleverly designed assay formats using these technologies are available commercially for the detection in foods of practically all major established pathogens and toxins, as well as of many emerging pathogens. These tests range from very simple antibody-bound latex agglutination assays to very sophisticated DNA amplification methods. Although molecular biological assays are more specific, sensitive, and faster than conventional (often cultural) microbiological methods, the complexities of food matrices continue to offer unique challenges that may preclude the direct application of these molecular biological methods. Consequently, a short cultural enrichment period is still required for food samples prior to analysis with these assays. The greater detection sensitivity of molecular biological methods may also affect existing microbiological specifications for foods; this undoubtedly will have repercussions on the regulatory agencies, food manufacturers, and also consumers. The US government has the right to retain a nonexclusive royalty-free license in and to any copyright covering this article. Use of trade names is for identification only and does not imply an endorsement by the US FDA.     

Prediction Models in Configural Frequency Analysis

Configural frequency analysis models are presented for predicting a discrete criterion variable from combining 2 or more discrete predictor variables nonparametrically. Predictions are made via so-called prediction types which allow to predict a criterion class from combined predictor classes. Prediction types are implicitely defined as cells of a 2-dimensional contingeney table with rows as predictor combinations and columns as criterion classes. The CFA is extended for two criteria, and for stratified sampling.     

Brief report: Normal hematology values of Sykes monkeys (Cercopithecus mitis albogularis)

Hematologic values are presented for the Sykes monkey (Cercopithecus mitis albogularis). The values are, in general, similar to published findings for other primate species. Elevated hemoglobin, possibly caused by high altitude, was noted. Significant differences of several values between males and females are discussed.     

Genetic assessment of spatiotemporal evolutionary relationships and stocking effects in grayling (Thymallus thymallus, Salmonidae)

Domestically reared introduced (or escaped) individuals can have detrimental genetic effects on the indigenous populations into which they are released. Consequently, numerous studies have attempted to estimate whether non-native specimens have contributed to the gene pool of wild populations. So far, the key limiting factor of such studies has been their lack of appropriate baseline genetic material. Here, microsatellite DNA analyses of historical scale samples and contemporary wild and introduced populations were used to assess spatiotemporal population structure and stocking effects among endangered Lake Saimaa (eastern Finland) grayling ( Thymallus thymallus , Salmonidae). Significant decreases in genetic differentiation were detected between wild and introduced populations since the commencement of stocking in 1986. Accordingly, up to 15% of the contemporary wild grayling were confidently identified to be of pure hatchery origin, and recent hybridization between the hatchery and indigenous individuals appeared likely. Despite these clear genetic imprints of stocking, the contemporary populations exhibited evolutionary relationships congruent with the sampling locations, and up to 73% of contemporary individuals were identified to be of pure indigenous origin. The use of historical baseline material should prove efficient for monitoring gene flow between domesticated and wild populations in other species also, e.g. salmonids, game animals and plants.     

Testing Linear Contrasts of Means in Experimental Design Without Assuming Normality and Homogeneity of Variances

We investigate the efficiencies of TIKU'S (1967, 1980) modified maximum likelihood (MML) estimators of location and scale parameters of symmetric distributions and show that they are remarkably efficient (jointly). We develop test statistics (based on MML estimators), analogous to the classical tests based on sample means and variances, for testing the equality of two means (the population variances not necessarily equal). We show that these tests are remarkably robust to distributional assumptions and generally more powerful than the well-known nonparametric tests (WILCOXON , normal-score, KOLMOGOROV -SMIRNOV ). We generalize the results to testing linear contrasts of means in experimental design (the error variances not necessarily equal). We show that the analogous tests based on ‘adaptive’ robust estimators (wave, bisquare, HAMPEL ,) etc., GROSS (1976, and other ‘adaptive’ robust estimators) give misleading Type I errors.     

Some Results for the Normal Manova Linear Functional Relationships Model

Given the normal multivariate linear regression model Y = BX + E, with B subjected to the linear restrictions H BJ = W A, J known, W and H unknown, A known, the maximum likelihood estimates of H, B, W, are obtained. A likelihood ratio test criterion for testing H = H₀, W = W₀ is provided. The results are extended to the GMANOVA model. All results are obtained in terms of the original variates directly, unlike Healy (1980) who obtains the results for the MANOVA model in terms of the canonical transformations of the original variates.     

A New Statistical Goodness-of-Fit Test Based on Graphical Representation

A statistical goodness-of-fit test, based on representing the sample observations by linked vectors, is developed. The direction and the length of the linked vectors are defined as functions of the expected values of the order statistics and sample order statistics, respectively. The underlying method can be used to test distributional assumptions for any location-scale family. A test statistic Q_n is introduced and some of its properties are studied. It is shown that the proposed test can be generalized to test if two or more independent samples come from the same distribution. The test procedure provides a graphical method of identifying the true distribution when the null hypothesis is rejected.