Statistical modelling of skewed and semi-continuous data in randomised controlled trials (RCTs): An application of two-part models in RCTs of chronic

Chronic pain is pain that persists beyond the normal time of healing, and can occur even when no obvious cause can be found with estimates suggesting 14 million people live with chronic pain in the UK and the global burden of pain related conditions increasing with an increasing elderly population.
The use of inappropriate analytical techniques seriously affects the findings of RCTs and will at best the precision of effect estimates will be reduced; at worst results might be grossly misleading.
Two-part models are a flexible modelling framework often used in econometrics for data with a large number of zeroes and non-zero values that are highly skewed or non-normal.
The goal of the research will be to develop and assess the application of two-part models in the context of outcomes that measure pain, and pain related disability, in musculoskeletal RCTs.
Performance of two-part models will be explored by fitting these models to simulated data to fully assess the bias and accuracy of estimates of treatment effects and their performance will be assessed by generating simulated datasets.
The increased flexibility of two-part models is expected to lead to better fitting models for pain data and thereby, most importantly, more reliable inference.