Since testing for COVID-19 infections is not at all randomized over the general population, most epidemiological model forecasts of deaths are subject to `selection bias.' This paper updates and supplements Vinod and Theiss (2020), where the bias correction using generalized linear models (GLM)...

We offer state-wise forecasts of COVID-19 pandemic deaths for the week ending August 10, 2020 based on a sample selection model to correct for rationed and biased testing for the virus. We refer the reader to our earlier papers including Vinod and Theiss (2020b) and Vinod and Theiss (2020a),...

Official guidelines for opening America after COVID-19 lockdowns are backward-looking. For example, they require a two-week downward trajectory of documented cases, without mentioning their statistical significance. We propose a forward-looking strategy using out-of-sample forecasts of deaths,...

Complete novelty and uncertainty of the COVID-19 pandemic have created many challenging scientific problems, including biased data arising from a lack of randomized testing over the general population. We describe the bias problem and its solution from Econometrics literature, which seems to...