Assessing the adequacy of Weibull survival models: a simulated envelope approach

The Weibull proportional hazards model is commonly used for analysing survival data. However, formal tests of model adequacy are still lacking. It is well known that residual-based goodness-of-fit measures are inappropriate for censored data. In this paper, a graphical diagnostic plot of Cox–Snell residuals with a simulated envelope added is proposed to assess the adequacy of Weibull survival models. Both single component and two-component mixture models with random effects are considered for recurrent failure time data. The effectiveness of the diagnostic method is illustrated using simulated data sets and data on recurrent urinary tract infections of elderly women

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach

Proceedings of The HKIE Geotechnical Division 41st Annual Seminar: Adapt to Challenges, Create to Thrive

This seminar proceedings contains articles on the various research ideas of the academic community and practitioners presented at The HKIE Geotechnical Division 41st Annual Seminar (GDAS2021). GDAS2021 was jointly organized by the Geotechnical Division, The Hong Kong Institution of Engineers, & The Hong Kong Geotechnical Society on July 18th May 2021. Seminar Title: The HKIE Geotechnical Division 41st Annual SeminarSeminar Acronym: GDAS2021Seminar Date: 18 May 2021Seminar Location: Online (Virtual Mode)Seminar Organizers: Geotechnical Division, The Hong Kong Institution of Engineers, & The Hong Kong Geotechnical Society