Date: April 16-18 2024, 10.00 AM (2 x 90 min)
Instructor: Levente Littvay (TK PTI)
Location: Centre for Social Sciences - 1097 Budapest, Tóth Kálmán u. 4.,
Institute for Political Science - meeting room (T.2.37.)
Number of participants: max. 30 person
Course language: English
Building on our last session, where we reviewed the assumptions of regression models, we will start to explore OLS regression in the presence of interactions, the estimators and link functions necessary to deal with binary, ordered, and unordered (multinomial) outcomes with a specific emphasis on the correct interpretation of such regression results. Second, we venture into the complexities of various data structures that emerge in voting behavior research, cross-country surveys, repeated cross-sectional surveys, panel data, or other within-person analyses. We will approach this complexity through three tools: clustered standard errors, fixed and random effects corrections, also moving into the world of multilevel modeling. In addition, we will also consider the (admittedly frustrating) topic of survey weights and discuss considerations and limitations in their applications.
Pre-requisites
For the applications, I use R, so basic R knowledge is strongly recommended. At least, you should be able to load a dataset and run a simple lm command. If you don’t know how to do this, please get there before the workshop. (This is not much work, you can definitely do it on your own.) Also, once you know what you are doing, you can easily transfer your knowledge to the analysis tools of your preference. If you missed the previous introductory regression workshop, please review Lewis-Beck and Lewis-Beck’s Applied Regression: An Introduction (second edition) or any other coveted introductory regression text and John Fox’s Regression Diagnostics book, both from SAGE’s Quantitative Applications in the Social Sciences (little green book) series.