ABSTRACT
This chapter aims to provide researchers with proper steps for running a Regression discontinuity (RD) design for cross-sectional and longitudinal data, as well as intervention research. It describes a process for conducting an RD design with illustrative examples using empirical data in both general and special education, highlighting two software packages, R and STATA. R rddtools package offers a set of tools to run almost all of the steps required for an RD design, from primary graphical representation including McCrary's density test, to RD design estimates, sensitivity, and placebo testing. R rdrobust package provides both statistical inference and graphical procedures employing local polynomial and partitioning methods. Moreover, it includes functions for sharp, fuzzy, and kink RD designs with RD plots. The chapter also discusses the primary advantages and disadvantages of RD and describes the assumptions that must be met in order to apply RD in appropriate contexts.
