Abstract
Analytical sociology explains macro-level outcomes by referring to micro-level behaviors, and its hypotheses thus take macro-level entities (e.g. groups) as their units of analysis. The statistical analysis of these macro-level units is problematic, since macro units are often few in number, leading to low statistical power. Additionally, micro-level processes take place within macro units, but tests on macro-level units cannot adequately deal with these processes. Consequently, much analytical sociology focuses on testing micro-level predictions. We propose a better alternative; a method to test macro hypotheses on micro data, using randomization tests. The advantages of our method are (i) increased statistical power, (ii) possibilities to control for micro covariates, and (iii) the possibility to test macro hypotheses without macro units. We provide a heuristic description of our method and illustrate it with data from a published study. Data and R-scripts for this paper are available in the Open Science Framework (https://osf.io/scfx3/).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.