Publications by Keith Goldfeld
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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The case of three MAR mechanisms: when is multiple imputation mandatory?
I thought I’d written about this before, but I searched through my posts and I couldn’t find what I was looking for. If I am repeating myself, my apologies. I explored missing data two years ago, using directed acyclic graphs (DAGs) to help understand the various missing data mechanisms (MAR, MCAR, and MNAR). The DAGs provide insight into whe...
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Generating random lists of names with errors to explore fuzzy word matching
Health data systems are not always perfect. This was made painfully obvious when a study I am involved with required a matched list of nursing home residents taken from one system with set results from PCR tests for COVID-19 drawn from another. Name spellings for the same person from the second list were not always consistent across different PCR...
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Sample size determination in the context of Bayesian analysis
Given my recent involvement with the design of a somewhat complex trial centered around a Bayesian data analysis, I am appreciating more and more that Bayesian approaches are a very real option for clinical trial design. A key element of any study design is sample size. While some would argue that sample size considerations are not critical to th...
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Estimating a risk difference (and confidence intervals) using logistic regression
The odds ratio (OR) – the effect size parameter estimated in logistic regression – is notoriously difficult to interpret. It is a ratio of two quantities (odds, under different conditions) that are themselves ratios of probabilities. I think it is pretty clear that a very large or small OR implies a strong treatment effect, but translating th...
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Fitting your model is only the beginning: Bayesian posterior probability checks with rvars
Say we’ve collected data and estimated parameters of a model that give structure to the data. An important question to ask is whether the model is a reasonable approximation of the true underlying data generating process. If we did a good job, we should be able to turn around and generate data from the model itself that looks similar to the dat...
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