A critical step in group sequential designs is computation of the appropriate critical values for rejecting H0 at the interim look to keep the overall type I error rate at a prespecified level. When applying the sequential test in a study with an equivalence hypothesis, calculation of the...

Both in classical multivariate analysis and in modern copula modeling, correlation matrices are a central concept of dependence modeling using multivariate normal distributions and copulas. Since the number of correlation parameters quadratically increases with the number of variables,...

A general statistical model for ordinal or rating data, which includes some existing approaches as special cases, is proposed. The focus is on the CUB models and a new class of models, called Nonlinear CUB, which generalize CUB. In the framework of the Nonlinear CUB models, it is possible to...

The efficiency of a marginal likelihood estimator where the product of the marginal posterior distributions is used as an importance sampling function is investigated. The approach is generally applicable to multi-block parameter vector settings, does not require additional Markov Chain Monte...

Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequently obtained by questionnaires in ordinal scales. To understand the relationship between explanatory variables and outcome measures, generalized estimating equations can be applied to provide a...

Measuring the accuracy of diagnostic tests is crucial in many application areas, in particular medicine and health care. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate among three ordered classes or groups....

The unknown error density of a nonparametric regression model is approximated by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. Such a mixture density has the form of a kernel density estimator of error realizations. An...

A new classifier, QIFC, is proposed based on the quadratic inference function for longitudinal data. Our approach builds a classifier by taking advantage of modeling information between the longitudinal responses and covariates for each class, and assigns a new subject to the class with the...

Many variables of interest in business and agricultural surveys have skewed distributions. Small area estimation methods are investigated under an assumption that the lognormal model is a reasonable approximation for the distribution of the response given covariates. Closed form expressions for...

A modified conditional Metropolis–Hastings sampler for general state spaces is introduced. Under specified conditions, this modification can lead to substantial gains in statistical efficiency while maintaining the overall quality of convergence. Results are illustrated in two settings: a toy...