Methods Setting: Pediatric Emergency Department (ED) of a Community hospital with around 10500 ED visits annually. The hospital conducts DNB Pediatrics, MCEM and BSc Accident & Emergency Technology Courses. Participants: 784 Children with accidental injuries between 0 and 18 years of age who attended ED in a 10-month period from January 2013 to October 2013. Design: Retrospective observational ...

We address the estimation of Markov (and semi-Markov) switching linear mixed models i.e. models that combine linear mixed models with individualwise random effects in a (semi-)Markovian manner. A MCEM-like algorithm whose iterations decompose into three steps (sampling of state sequences given random effects, prediction of random effects given the state sequence and maximization) is proposed. T...

High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, w...

Difference of convex functions (DC) programming is an important approach to nonconvex optimization problems because these structures can be encountered in several fields. Effective optimization methods, called DC algorithms, have been developed in deterministic optimization literature. In machine learning, a lot of important learning problems such as the Boltzmann machines (BMs) can be formulat...

We propose a new stochastic approximation (SA) algorithm for maximum likelihood estimation (MLE) in the incomplete data setting. This algorithm is most useful for problems when the EM algorithm is not possible due to an intractable E-step or M-step. Compared to other algorithms that have been proposed for intractable EM problems such as the MCEM algorithm of Wei and Tanner (1990), our proposed ...

In clinical trials and other follow-up studies, it is natural that a response variable is repeatedly measured during follow-up and the occurrence of some key event is also monitored. There has been a considerable study on the joint modelling these measures together with information on covariates. But most of the studies are related to continuous outcomes. In many situations instead of observing...

It is often the case in modeling biological phenomena that the structure and the effect of the involved interactions are known but the rates of the interactions are neither known nor can easily be determined by experiments. This paper deals with the estimation of the rate parameters of reaction networks in a general and abstract context. In particular, we consider the case in which the phenomen...

This article develops a full maximum likelihood method for obtaining joint estimates of variances and correlations among continuous and polytomous variables with incomplete data which are missing at random with an ignorable missing mechanism. The approach for obtaining the maximum likelihood estimate of the covariance matrix is via a simple confirmatory analysis model with a fixed identity load...

Most MRCP and MRCS Part 1 candidates would be advised to invest in a Sainsbury's shopping trolley if they decide to venture to their local university bookshop in pursuit of a relevant MCQs textbook. The shelves of these stores creak from the burden of the wide selection of texts. The unfortunate MCEM / MRCS A&E candidate will be left with growing anxiety and the knowledge that there are very fe...