This problem comes up a lot: We have multiple surveys of the same population and we want a single inference. The usual approach, applied carefully by news organizations such as Real Clear Politics and Five Thirty Eight, and applied sloppily by various attention-seeking pundits every two or four years, is “poll aggregation”: you take the […]
Continuing from our earlier discussion . . . Yair posted some results from his MRP analysis of voter turnout: 1. The 2018 electorate was younger than in 2014, though not as young as exit polls suggest. 2. The 2018 electorate was also more diverse, with African American and Latinx communities surpassing their share of votes […]
John Spivack writes: I am contacting you on behalf of the biostatistics journal club at our institution, the Mount Sinai School of Medicine. We are working Ph.D. biostatisticians and would like the opinion of a true expert on several questions having to do with observational studies—questions that we have not found to be well addressed […]
The post Matching (and discarding non-matches) to deal with lack of complete overlap, then regression to adjust for imbalance between treatment and control groups appeared first on Statistical Modeling, Causal Inference, and Social Science.
We’re always discussing election results on three levels: their direct political consequences, their implications for future politics, and what we can infer about public opinion. In 2018 the Democrats broadened their geographic base, as we can see in this graph from Yair Ghitza: Party balancing At the national level, what happened is what we expected […]
The post 2018: What really happened? appeared first on Statistical Modeling, Causal Inference, and Social Science.
Benjamin Carlisle writes: A year ago, I received a message from Anna Powell-Smith about a research paper written by two doctors from Cambridge University that was a mirror image of a post I wrote on my personal blog roughly two years prior. The structure of the document was the same, as was the rationale, the […]
The post “Recapping the recent plagiarism scandal” appeared first on Statistical Modeling, Causal Inference, and Social Science.
Melanie Miller‘s piece, Artificial Intelligence Hits the Barrier of Meaning (NY Times behind limited paywall), is spot-on regarding the hype surrounding the current A.I. boom. It’s soon to come out in book length from FSG, so I suspect I’ll hear about it again in the New Yorker. Like Professor Miller, I started my Ph.D. at […]
The post Melanie Miller says, “As someone who has worked in A.I. for decades, I’ve witnessed the failure of similar predictions of imminent human-level A.I., and I’m certain these latest forecasts will fall short as well. “ appeared first on Statistical Modeling, Causal Inference, and Social Science.