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A great opportunity to learn Stata and Statistics from an expert!
Information, Technology & Consulting and StataCorp co-sponsor the following Stata Webinar:
Date: March 24
Time: 13:00 - 15:00 EST
Registration link: https://libcal.dartmouth.edu/calendar/itc/statadayatdartmouth2022
1. Panel Data and Mixed Effects Models: What's the Difference? (60 minutes)
Clustered and repeated measures data are common in all scientific disciplines. Data analysts in various disciplines have developed methods for modeling these kinds of data but differences in terminology make it challenging to understand the similarities and differences among these methods. For example, behavioral and biomedical researchers often use "multilevel", "hierarchical", or "mixed effects" methods to model "longitudinal data" while economists often favor "fixed effects" models and "cluster robust standard errors" for modeling "panel data". This talk will define each of these methods conceptually, describe the similarities and differences between them, and identify the situations where each are appropriate.
2. Missing Data and Multiple Imputation (60 minutes)
In this talk I introduce different kinds of mechanisms that lead to missing data such as missing at random (MAR), missing completely at random (MCAR), and missing not at random (MNAR). I then demonstrate how to use Stata's -mi- commands to impute missing data and fit models using the imputed datasets.
Chuck Huber is the Director of Statistical Outreach at StataCorp and an Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata YouTube channel, writes blog entries, develops online NetCourses, and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by psychologists and other behavioral scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition, and birth defects.
All registered participants will receive a zoom link prior to the webinar.
If you have any questions about this event, please email Jianjun at firstname.lastname@example.org.
Events are free and open to the public unless otherwise noted.