2 citations · 3 across the 5 of their papers we have counts for
5 papers
Modelling the Spatially Varying Non-Linear Effects of Heat Exposure
Xinyi Chen, Marta Blangiardo, Connor Gascoigne +1
Exposure to high ambient temperatures is a significant driver of preventable mortality, with non-linear health effects and elevated risks in specific regions. To capture this compl…
Smoothing for age-period-cohort models: a comparison between splines and random process
Connor Gascoigne, Theresa Smith, Andrea Riebler
Age-Period-Cohort (APC) models are well used in the context of modelling health and demographic data to produce smooth estimates of each time trend. When smoothing in the context o…
Estimating Subnational Under-Five Mortality Rates Using a Spatio-Temporal Age-Period-Cohort Model
Connor Gascoigne, Theresa Smith, John Paige +1
Producing subnational estimates of the under-five mortality rate (U5MR) is a vital goal for the United Nations to reduce inequalities in mortality and well-being across the globe.…
Bayesian Interrupted Time Series for evaluating policy change on mental well-being: an application to England's welfare reform
Connor Gascoigne, Marta Blangiardo, Zejing Shao +4
Factors contributing to social inequalities are also associated with negative mental health outcomes leading to disparities in mental well-being. We propose a Bayesian hierarchical…
Using smoothing splines to resolve the curvature identifiability problem in age-period-cohort models with unequal intervals
Connor Gascoigne, Theresa Smith
Age-period-cohort (APC) models are frequently used in a variety of health and demographic related outcomes. Fitting and interpreting APC models to data in equal intervals (equal ag…