failure mode and effects analysis (fmea) is a method based on teamwork to identify potential failures and problems in a system, design, process and service in order to remove them. the important part of this method is determining the risk priorities of failure modes using the risk priority number (rpn). however, this traditional rpn method has several shortcomings. therefore, in this paper we p...

menorrhagia is one of the most common gynecological problem and leading causes of poor quality of life and iron deficiency anemia in women of reproductive age. research in gynecological field relies heavily on repeated measure designs. repeated measure studies are helpful in understanding how factors of interest change over time. our goal is to apply statistical methods which are appropriate fo...

I investigate, using the R package spaMM, the effect of misspecification of the smoothing parameter, , of the Matern covariance structure on the mean part of hierarchical generalised linear models (HGLMs) with spatially correlated Gaussian Matern random effects. In particular, by restricting to the set {0.5, 1.5, 2.5} I examine via a simulation study the amount of bias introduced on the fixed e...

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of inte...

Generalized linear mixed models are popular to regress a discrete response when there is clustering, e.g. in longitudinal studies or in hierarchical data structures. It is standard to assume that the random effects have a normal distribution. Recently, it has been examined whether wrongly assuming a normal distribution for the random effects is important for the estimation of the fixed effects ...

This study introduces new methods of screening for and tuning chiral space and in so doing identifies a promising set of chiral ligands for asymmetric synthesis. The carbafructopyranosyl-1,2-diamine(s) and salens constructed therefrom are particularly compelling. It is shown that by removing the native anomeric effect in this ligand family, one can tune chiral ligand shape and improve chiral bi...

This vignette describes the R hglm package via a series of applications that may be of interest to applied scientists. The hglm package implements the estimation algorithm for hierarchical generalized linear models. The package fits generalized linear models with random effects, where the random effect may come from a conjugate exponential-family distribution (Gaussian, Gamma, Beta or inverse-G...