In situations where a large data set is partitioned into many relatively small groups, and you want to test for group differences, the number of parameters tend to increase with sample size. This fact causes the standard assumptions underlying asymptotic results to be violated. There are (at least) two possible solutions to the problem, first, a random intercepts model, and second, a fixed effe...

We propose a class of double hierarchical generalized linear models in which random effects can be specified for both the mean and dispersion. Heteroscedasticity between clusters can be modelled by introducing random effects in the dispersion model, as is heterogeneity between clusters in the mean model.This class will, among other things, enable models with heavy-tailed distributions to be exp...

Marginalised models, also known as marginally specified models, have recently become a popular tool for analysis of discrete longitudinal data. Despite being a novel statistical methodology, these models introduce complex constraint equations and model fitting algorithms. On the other hand, there is a lack of publicly available software to fit these models. In this paper, we propose a three-lev...

The recent literature on measuring bank performance indicates a preference for sophisticated techniques over simple accounting ratios. We explore the results and relationships between bank efficiency estimates using accounting ratios and Data Envelope Analysis (DEA) with bootstrap among Jamaican banks between 1998 and 2007. The results indicate different outcomes for the traditional accounting ...

Here we studied the performances of some of the available analytic methods applicable to the analysis of proportion data; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report the conclusions from a simulation study evaluating power and Type I error rates of these models in scenarios akin to those met by behavioral research...

The penalized quasi-likelihood (PQL) approach is the most common estimation procedure for the generalized linear mixed model (GLMM). However, it has been noticed that the PQL tends to underestimate variance components as well as regression coefficients in the previous literature. In this paper, we numerically show that the biases of variance component estimates by PQL are systematically related...

The first total synthesis of dinemasone A, a bioactive metabolite with a spiroketal moiety, is described. The main strategy for the construction of the spiroketal unit involves a double intramolecular hetero-Michael addition (DIHMA) of an ynone moiety. The thus obtained axial-equatorial mono anomeric spiroketal, on spiroepimerization with ZnBr(2), was converted into the requisite axial-axial do...

In tumoral cells derived from the insulin-producing rat cell line RINm5F, both low- and high-Km glucose-phosphorylating enzymic activities were present. The hexokinase-like enzyme was inhibited by glucose 6-phosphate and displayed a greater affinity for but lower maximal velocity with alpha-D-glucose than beta-D-glucose. A comparable anomeric behavior of hexokinase was observed in breast cancer...

We introduce a flexible marginal modelling approach for statistical inference for clustered/longitudinal data under minimal assumptions. This estimated estimating equations (EEE) approach is semiparametric and the proposed models are fitted by quasi-likelihood regression, where the unknown marginal means are a function of the fixed-effects linear predictor with unknown smooth link, and variance...