[Hybrid] Missing Data Treatment in R: A Hands-on Illustration Using {mice}

[Note]
Come join us for our first in-person event in over two years! This event will take place at Rebel (Universitetsgata 2, Oslo), in room "Elizabeth" (kursrom 3). We cannot wait to meet all of you again and celebrate more than 2,000 members!

For those of you joining us elsewhere in the world, you can livestream the event here: https://www.youtube.com/watch?v=BZIHHR-V4wg

[Abstract]
Missing data is the norm rather than exception in most real-life data sets. It is not only wasteful to exclude observations that contain missing values but also opens parameter estimations to potential inconsistency and bias. This meetup focuses on the fully conditional specification technique using the R package {mice} (multivariate imputation by chained equations). We will be introduced to different missing data mechanisms, their impact on estimations, and the corresponding coping strategies. We will then take a look at {mice}, particularly its functionalities for imputing missing data, and eventually showcase how to analyze imputed datasets and how to interpret the results.

[Bio]
The speaker, Tony Tan is a PhD candidate at Centre for Educational Measurement (CEMO), University of Oslo. He holds Economics and Accounting degrees from the Australian National University and a teaching degree from the University of Melbourne.