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For modelling the effect of crossed, fixed factors on the response variable in balanced designs with nested stratifications, a generalized linear mixed model is proposed. This model is based on a set of quasi‐likelihood assumptions which imply quadratic variance functions. From these variance functions, deviances are obtained to quantify the variation per stratification. The effects of the fixed factors will be tested, an dispersion components will be estimated. The practical use of the model is illustrated by reanalysing a soldering failures problem.

In this paper a review will be given of some methods available for modelling relationships between categorical response variables and explanatory variables. These methods are all classed under the name polytomous logistic regression (PLR). Models for PLR will be presented and compared; model parameters will be tested and estimated by weighted least squares and by likelihood. Usually, software is needed for computation, and available statistical software is reported.An industrial problem is solved to some extent as an example to illustrate the use of PLR. The paper is concluded by a discussion on the various PLR‐methods and some topics that need a further study are mentioned.

From the literature on nonparametric rank tests, limiting distributions of Wilcoxon's test tor symmetry and ot Friedman's test for treatment effect are known for observations that are classified in blocks. It is assumed that there is no interaction between blocks and treatments. In the case of fixed blocks this assumption is quite reasonable, in the case of random blocks it is not, as the presence of a random interaction does not make testing for treatment effect superfluous. For classified, categorical data in random blocks the limiting distribution will be derived in this paper of Wilcoxon's rank test in a model which includes a random interaction between blocks and treatments.An illustration is given by some data from a judgement comparison experiment for the image quality of Video Long Play discs.

AbstractThe analysis of count response data from designed experiments is well–known for independent response variables having the Poisson distribution. For experimental designs where responses are dependent, no general results seem to be available. An example of this type of design is the split–plot design, where sub–plot responses are essentially dependent within whole plots.In this paper, a model will be proposed for split–plot count data and a separate analysis for whole plot and sub–plot data will be presented. It is interesting to note, that the same model is used in the quite different context of consumer buying behaviour. It is derived by Goodhardt, Ehrenberg and Chatfield and it was called the 'Dirichlet model', as the Dirichlet multinomial distribution, together with the negative binomial distribution, build up the model.

AbstractThe beta–binomial distribution is reported in literature as a useful generalization of the binomial in case of heterogeneous binomial sampling. An extra model parameter is introduced to accommodate for extra–binomial variation. Some additions to results already available will be given by presenting approximate F–tests for factorial designs, where the response variable is of 0–1 type and sampling is heterogeneous binomial. These tests can be used when sample sizes are large and equal and some degrees of freedom are left from replicates or negligible interactions to estimate the extra model parameter.

Abstract  When observations from a normal distribution can only be obtained indirectly by counting the number of subjects responding to a previously chosen dose, parameter estimates can be obtained by using probit analysis. Well‐known is the maximum likelihood technique of parameter estimation, less known is the approach by weighted least squares. The latter approach is followed to compare the parameters of several normal distributions by testing their equality, in analogy with the analysis of variance. A practical situation gave rise to this study and it is worked out at the end of the paper.

AbstractThere is increasing conviction that to enjoy and promote the mutual fl ourishing of human life in mutual relationship to the fl ourishing of all life on Earth is the ultimate meaning of human history. Yet the contemporary human condition is one of profound alienation from that meaning. The metaphor and model of a new global covenant, a new covenant with Earth, provides the most constructive and practical way individuals and communities can respond to this spiritual situation, and inspires e ff orts such as the Earth Charter, and draft International Covenant on Environment and Development, to articulate a new global ethic. The new model of Earth covenant has emerged over a long course of history from interactions between Earth-affirming religious sensibilities, evolutionary/ecological understandings, and democratic ideals. Although it is still very much in the making, and requires much wider global dialogue, we can extrapolate ten major normative themes central to the new covenantal vision.