The field of replication studies remains a controversial, misunderstood, and unappreciated piñata of 18 replication typologies, spanning 79 replication types. To help bring order into chaos I contribute a theory of manufactured inferences. The theory is built on three pillars: (i) replication...

Estimating the effect of macro variables like democracy on aggregate outcomes like child mortality remains a formidable challenge. When new data are limited, theories imprecise, and experimentation impossible, findings are mostly driven by modeling assumptions and inadvertent errors. Here I...

The fundamental problem of external validity is not to generalize from one experiment, so much as to experimentally test generalizable theories. That is, theories that explain the systematic variation of causal effects across contexts. Here we show how the graphical language of causal diagrams...

The fundamental problem of external validity is not to generalize from one experiment, so much as to experimentally test generalizable theories. That is, theories that explain the systematic variation of causal effects across contexts. Here we show how the graphical language of causal diagrams...

Randomized controlled trials and natural experiments have been criticized for their lack of generalizability (external validity), questioning their usefulness to social science and policy. Here I show how three common approaches to generalizability -- the heuristic, statistical, and structural...

Theories of democratic accountability predict a positive effect of democracy on health outcomes. This prediction is at odds with published empirical estimates, which range from impossibly large to null effects, in part due to missing data, extreme counterfactuals, and lack of attention to...

Attrition is the Achilles' Heel of the randomized experiment: It is fairly common, and it can completely unravel the benefits of randomization. Using the structural language of causal diagrams I demonstrate that attrition is problematic for identification of the average treatment effect (ATE) if...

Attrition is the Achilles’ Heel of the randomized experiment: it is fairly common, and it can unravel the benefits of randomization. This study considers when and why attrition is a problem, and how it can be diagnosed. The extant literature remains ambiguous because it relies on the language...

Attrition is the Achilles' Heel of the randomized experiment: It is fairly common, and it can completely unravel the benefits of randomization. Using the structural language of causal diagrams I demonstrate that attrition is problematic for identification of the average treatment effect (ATE) if...