Administrative data and data linkage; collecting health
data for econometric analysis; categorical data methods; count data; duration analysis; econometric evaluation by non-experimental methods; econometric evaluation with randomized experiments; econometrics in technology assess- ment; macro panels; models of health care costs; models for risk adjustment; panel data methods; productivity analysis; simulation methods and mixture models; spatial econometrics.
It is a contentious issue in philosophy whether an omission can be the cause of an event. At the very least it seems we should consider causation by omission differently from ‘ordinary’ causation. Consider Sarah McGrath’s example. Billy promised Alice to… Read More »Are we estimating the effects of health care expenditure correctly?
The patient reported outcomes measures, or PROMs, is a large database with before and after health-related quality of life (HRQoL) measures for a large number of patients undergoing four key conditions: hip replacement, knee replacement, varicose vein surgery and surgery… Read More »Visualising PROMs data
Variations in admissions to NHS hospitals are the source of a great deal of consternation. Over the long-run, admissions and the volume of activity required of the NHS have increased, without equivalent increases in funding or productivity. Over the course… Read More »Variations in NHS admissions at a glance
The statistics underlying the arguments around the weekend effect are complicated. Despite over a hundred empirical studies on the topic, and an observed increase in the risk of mortality for weekend admissions in multiple countries, there is still no real… Read More »Weekend effect explainer: why we are not the ‘climate change deniers of healthcare’
Social scientists, especially economists, are concerned with causal inference: understanding whether and how an event causes a certain effect. Typically, we subscribe to the view that causal relations are reducible to sets of counterfactuals, and we use ever more sophisticated… Read More »Transformative treatments: a big methodological challenge for health economics
One of the advantages of writing blogs is that it can help to refresh and consolidate you thoughts on a topic. And when you spend a lot of time writing stats code, other people’s blogs that discuss how to code specific… Read More »Geostatistical modelling with R and Stan
Yesterday I explored one of the major challenges to affordable, universal health insurance, namely the high cost of providing care to the sickest patients. The extreme distribution of healthcare costs means that “Targeting the highest spenders represents the greatest opportunity… Read More »“Doing the math” on the distribution of healthcare expenditures: a Pareto-like distribution is inevitable
Slums are a large and growing feature of urban areas in low and middle income countries. But, despite the ease with which you might picture what such informal settlements look like, there is no consensus about what exactly defines a… Read More »The health of people who live in slums and the trouble with estimating neighbourhood effects
David Colquhoun, professor of pharmacology at UCL, has a new essay over at Aeon opining about the problems with p-values. A short while back, we also discussed p-value problems, and Colquhoun arrives at the same conclusions as us about the… Read More »Placebos for all, or why the p-value should have no place in healthcare decision making
The world’s highest impact factor medical journal, the New England Journal of Medicine (NEJM), seems to have been doing some soul searching. After publishing an editorial early in 2016 insinuating that researchers requesting data from trials for re-analysis were “research parasites“,… Read More »Data sharing and the cost of error