A fully parametric copula model for symmetric dependent clustered categorical data is discussed. The model accommodates any marginal regression models of interest and admits a broad range of within-cluster association. The form of the distribution is independent of cluster size and may be used to model data with varying cluster sizes. The model contains an association parameter that is estimated from the data to give a measure of strength of the within-cluster association and also a test of independence. Two examples are given to illustrate methods.

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This work describes an orthogonal array (OA8) designed experiment involving several insitu process perturbations during oxidation to develop a 90 Å gate oxide for 0.5μm CMOS technology. The biggest impactors were (i) the insitu preoxidation anneal at oxidation temperature, Tox, (ii) 90% N2 dilution of the ambient during ramp-up, and (iii) lowering the Tox to 850°C. Significant improvements in leakage, breakdown, and wear-out characteristics of the oxide are probably due to the reduction of poor quality ramp oxide grown by 90% N2 dilution and improved Si/SiO2 interfacial substructure attained by the insitu preoxidation anneal.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Biometrika Trust is collaborating with JSTOR to digitize, preserve and extend access to Biometrika. SUMMARY Goodness-of-fit tests are provided for the assumption of homoscedastic normal errors in experimental designs where the number of fitted parameters is large. Asymptotic critical points are given for the Cramer-von Mises statistic, Watson's statistic and the Anderson-Darling statistic. An expansion of the covariance function of the empirical process of standardized residuals is given. The corresponding weak convergence result is established for one-way layouts when the number of parameters grows linearly with the sample size. A Monte Carlo study is given to aid in the use of the tables. Some key words: Anderson-Darling statistic; Cramer-von Mises statistic; Goodness-of-fit; Watson's statistic.

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