In observational studies, selection bias will be completely removed only if the selection mechanism is ignorable, namely, all confounders of treatment selection and potential outcomes are reliably measured. Ideally, well-grounded substantive theories about the selection process and outcome-generating model are used to generate the sample of…

Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…

The nested data structure inherent in education (i.e. students nested in schools nested in districts) makes intact school matching an appealing approach in observational studies of educational interventions and policies for both theoretical and practical purposes. This paper provides guidance to applied education researchers who are employing…

The assumption of strongly ignorable treatment assignment is required for eliminating selection bias in observational studies. To meet this assumption, researchers often rely on a strategy of selecting covariates that they think will control for selection bias. Theory indicates that the most important covariates are those highly correlated with…

How some of the past literature creates the impression of an inevitable method-paradigm linkage and of a forced choice between qualitative and quantitative paradigms is shown. Difficulties of making method choices are considered. It is suggested that purposefully developed strengths of different methods should not be ignored. (Author/GK)