Machine Learning in Survey Research
August 19, 2021
PDHP resumes our 2021 workshop series on Thursday, August 19th, with a workshop entitled Introduction to Multilevel Models, presented by Dr. Kris Preacher of Vanderbilt University’s Quantitative Methods program (within the Department of Psychology and Human Development). This half-day workshop is geared toward data analysts and researchers of all levels, particularly those performing analysis on hierarchically clustered (nested) data using Mplus, R, or SPSS. Attendees will receive an introduction to the key concepts of multilevel models (appropriate settings for their use over standard statistical models, equation conventions, and interpretation), as well as hands-on practice implementing state-of-the-art features of MLM using popular statistical software packages.
- Key concepts and motivation for MLM vs. standard statistical models
- Estimating and plotting interaction effects
- Implications of nested vs. cross-classified mutlilevel data
- Power analysis for MLM using a general Monte Carlo technique
Slides & Lab Materials:
NOTE: This workshop primarily introduces concepts and does not assume proficiency in any particular software. Workshop examples are primarily drawn from R and SPSS, and supplementary code (linked above) is provided for Mplus, R, and SPSS.
–Mplus users: Supplemental code requires Mplus Base Program + Multilevel Add-On
–R users: Supplemental code requires lme4 package (install code below)
## install packages install.packages("lme4")
–SPSS users: Supplemental code uses the Advanced Statistics module within SPSS.