orgtheory.net

understanding the prevalance of covid

On Twitter, Gabriel Rossman is interested in the issue of selection bias in a recent study of covid. What happens if a study is contaminated by selection bias?

Excellent point. But this is a problem with all surveys – not only do you have to randomly sample people, they have to randomly respond. Fortunately, there are ways to understand how survey participation biases estimation.

Strategy 1: If you have data on responders and non-responders (e.g., SES data on neighborhood, some basic demographic data), you can create a two stage model. This is the intuition behind the Heckman model.

Strategy 2: If you have some intuition on why people do not respond, you can simulate non-response and create bounds on your errors.

Strategy 3: Go full Bayesian. Admit that bias exists in the model but build that into an update on what you think the true parameters are.

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Written by fabiorojas

April 22, 2020 at 6:14 pm

Posted in uncategorized

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