This course and the textbook give students the necessary tools to calculate analysis weights for various survey designs in a real-world setting. We will cover topics on calculating base weights for single- and multistage designs, adjusting weights for unknown study eligibility and nonresponse using a few techniques, and aligning survey estimates with known population values through weight calibration.
We will use specialized software for the procedures mentioned. This course will emphasize R but some examples in SAS and Stata are also discussed. R is downloaded for free from http://cran.r-project.org/. Students may also find https://www.rstudio.com/ a helpful interface to execute program code. For those new to R, there are many MarinStatsLectures available at https://www.youtube .com/playlist?list=PLqzoL9-eJTNBDdKgJgJzaQcY6OXmsXAHU
There will be homework problems each week for students to gain practice using all methods covered in the course. The emphasis will be on using the methods to solve practical problems; we review theory as needed for a clear understanding of the underlying assumptions. All are encouraged to discuss their own weighting challenges and solutions during our weekly online meetings.
By the end of the course, students will understand:
Grading will based on
Sampling theory (e.g., SURV440), Sampling I (e.g., SURV626), or Practical Tools (Part II) for Sampling.
Some experience with variance estimation (e.g., SURV742), statistical analysis using survey data, and the R statistical computing software will be helpful.