My talk at this conference in honor of Lars Lyberg on 1 Dec:

There are two steps of sampling: design and analysis. Analysis should respect design (for example, accounting for stratification and clustering) and design should anticipate analysis (for example, collecting relevant background variables to be used in nonresponse adjustment). In recent decades, many techniques have been developed for inference from non-probability samples. We discuss what the existence of these methods implies for design and data collection. What is the role of probability sampling in this world?

P.S. Here’s the youtube of it. I can’t stand seeing myself on video, and I find non-live talks difficult to watch in any case. But here it is in case you want it.