Articles by Keith Goldfeld

Musings on missing data

April 1, 2019 | Keith Goldfeld

I’ve been meaning to share an analysis I recently did to estimate the strength of the relationship between a young child’s ability to recognize emotions in others (e.g. teachers and fellow students) and her longer term academic success. The study itself is quite interesting (hopefully it will ...
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Considering sensitivity to unmeasured confounding: part 1

January 1, 2019 | Keith Goldfeld

Principled causal inference methods can be used to compare the effects of different exposures or treatments we have observed in non-experimental settings. These methods, which include matching (with or without propensity scores), inverse probability weighting, and various g-methods, help us create comparable groups to simulate a randomized experiment. All of ...
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Horses for courses, or to each model its own (causal effect)

November 27, 2018 | Keith Goldfeld

In my previous post, I described a (relatively) simple way to simulate observational data in order to compare different methods to estimate the causal effect of some exposure or treatment on an outcome. The underlying data generating process (DGP) included a possibly unmeasured confounder and an instrumental variable. (If you ...
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Causal mediation estimation measures the unobservable

November 5, 2018 | Keith Goldfeld

I put together a series of demos for a group of epidemiology students who are studying causal mediation analysis. Since mediation analysis is not always so clear or intuitive, I thought, of course, that going through some examples of simulating data for this process could clarify things a bit. Quite ...
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