Generalized linear mixed models (GLMMs) are useful for modelling longitudinal and clustered data, but parameter estimation is very challenging because the likelihood may involve high-dimensional integrals that are analytically intractable. GaussHermite quadrature (GHQ) approximation can be applied but is only suitable for low-dimensional random effects. Based on the Quasi-Monte Carlo (QMC) appr...

The multiple repairable systems may present system-to-system variability owing to the factors such as operation environments and working intensities of individual systems. It may be more reasonable to assume a heterogeneity among all the systems. In this paper, we propose a nonlinear mixed-effects model (NLMM), called power law process-nonlinear mixed-effects model (PLP-NLMM) and log linear pro...

The paper discusses asymptotic properties of penalized spline smoothing if the spline basis increases with the sample size. The proof is provided in a generalized smoothing model allowing for non-normal responses. The results are extended in two ways. First, assuming the spline coefficients to be a priori normally distributed links the smoothing framework to generalized linear mixed models (GLM...

The co-twin control study is a popular research design that is used in many research disciplines, including epidemiology, medicine, and the behavioural sciences. In co-twin control studies of monozygotic (MZ) exposure discordant twin pairs, the appropriate statistical tests used to analyse data from continuous outcome variables are the parametric paired sample t test or the non-parametric Wilco...

BACKGROUND Patient safety culture (PSC) has an important role in determining safety and quality in healthcare. Currently, little is known about the status of unit-level PSC in hospitals in Japan. To develop appropriate strategies, characteristics of unit-level PSC should be investigated. Work units may be classified according to the characteristics of PSC, and common problems and appropriate st...

OBJECTIVE For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another exten...