Publications by Keith Goldfeld
Exploring the properties of a Bayesian model using high performance computing
An obvious downside to estimating Bayesian models is that it can take a considerable amount of time merely to fit a model. And if you need to estimate the same model repeatedly, that considerable amount becomes a prohibitive amount. In this post, which is part of a series (last one here) where I’ve been describing various aspects of the Bayesia...
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A latent threshold model to dichotomize a continuous predictor
This is the context. In the convalescent plasma pooled individual patient level meta-analysis we are conducting as part of the COMPILE study, there is great interest in understanding the impact of antibody levels on outcomes. (I’ve described various aspects of the analysis in previous posts, most recently here). In other words, not all convales...
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A Bayesian implementation of a latent threshold model
In the previous post, I described a latent threshold model that might be helpful if we want to dichotomize a continuous predictor but we don’t know the appropriate cut-off point. This was motivated by a need to identify a threshold of antibody levels present in convalescent plasma that is currently being tested as a therapy for hospitalized pat...
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Constrained randomization to evaulate the vaccine rollout in nursing homes
On an incredibly heartening note, two COVID-19 vaccines have been approved for use in the US and other countries around the world. More are possibly on the way. The big challenge, at least here in the United States, is to convince people that these vaccines are safe and effective; we need people to get vaccinated as soon as they are able to slow ...
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Coming soon: effortlessly generate ordinal data without assuming proportional odds
I’m starting off 2021 with my 99th post ever to introduce a new feature that will be incorporated into simstudy soon to make it a bit easier to generate ordinal data without requiring an assumption of proportional odds. I should wait until this feature has been incorporated into the development version, but I want to put it out there in case an...
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Finding answers faster for COVID-19: an application of Bayesian predictive probabilities
As we evaluate therapies for COVID-19 to help improve outcomes during the pandemic, researchers need to be able to make recommendations as quickly as possible. There really is no time to lose. The Data & Safety Monitoring Board (DSMB) of COMPILE, a prospective individual patient data meta-analysis, recognizes this. They are regularly monitoring t...
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How useful is it to show uncertainty in a plot comparing proportions?
I recently created a simple plot for a paper describing a pilot study of an intervention targeting depression. This small study was largely conducted to assess the feasibility and acceptability of implementing an existing intervention in a new population. The primary outcome measure that was collected was the proportion of patients in each study ...
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Visualizing the treatment effect with an ordinal outcome
If it’s true that many readers of a journal article focus on the abstract, figures and tables while skimming the rest, it is particularly important tell your story with a well conceived graphic or two. Along with a group of collaborators, I am trying to figure out the best way to represent an ordered categorical outcome from an RCT. In this cas...
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Randomization tests make fewer assumptions and seem pretty intuitive
I’m preparing a lecture on simulation for a statistical modeling class, and I plan on describing a couple of cases where simulation is intrinsic to the analytic method rather than as a tool for exploration and planning. MCMC methods used for Bayesian estimation, bootstrapping, and randomization tests all come to mind. Randomization tests are pa...
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Framework for power analysis using simulation
The simstudy package started as a collection of functions I developed as I found myself repeating many of the same types of simulations for different projects. It was a way of organizing my work that I decided to share with others in case they wanted a routine way to generate data as well. simstudy has expanded a bit from that, but replicability ...
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