Measurement error models address the deviation between observed and true values, thereby refining the reliability of statistical inference. These frameworks are ...

This article resulted from our participation in the session on the “role of expert opinion and judgment in statistical inference” at the October 2017 ASA Symposium on Statistical Inference. We present ...

"In this universe effect follows cause. I've complained about it, but. . ." -- House (Laurie), pre-sponding to D. Bem "The more extraordinary the event, the greater the need for it to be supported by ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning ...

The most widely used statistical inference procedures were invented more than 10 years ago and are not well suited for handling state-of-the art high-resolution neuroimaging data. MRI technology ...

This is a preview. Log in through your library . Abstract We present a general approach to statistical problems with criteria based on probabilities of large deviations. Our main idea, which ...

If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure ...