ABSTRACT
How do investigators identify the best research design to address their research question? Many researchers gravitate to designs for those data most easily available, a strategy that limits the rich menu of possible designs. A primary aim of this chapter is to provide decision heuristics to enable a wider range of design choice to enhance causal inference. The annotated bibliography provides relevant design references and high-quality exemplars. Rule-out conditions are given for each design along with important advantages and disadvantages. The chapter includes little used (regression point displacement), recently created (SMART: Sequential Multiple Allocation Research Trials) and new (Common Cause) designs. It concludes with explicit design directives aimed to maximize inferential quality, including embed multiple designs to address each research question; first use single-case then between-groups designs to evaluate interventions; “think in templates” to discover novel ways to address questions asked and answered in other disciplines; consider research opportunities in university settings to counter restricted design choice; and use design logic to mend research problems.
