Three quantitative methods are compared for their ability to understand different COVID-19 fatality ratios in 33 OECD countries. Linear regression provides a limited overview without sensitivity to the diversity of cases. Cluster Analysis and Dynamic Patterns Synthesis (DPS) gives scrutiny to the granularity of case similarities and differences,…

Causal asymmetry is a situation where the causal factors under study are more suitable for explaining the outcome than its absence (or vice versa); they do not explain both equally well. In such a situation, presence of a cause leads to presence of the effect, but absence of the cause may not lead to absence of the effect. A conceptual discussion…

Conventional approaches to causation in the social sciences draw on approaches in the Philosophy of Science in which a causal force acts on cases and generates change in the form of events. This relies on just one of the Aristotelian conceptions of cause - efficient cause - what brings the effect in to being. We should also pay attention to Final…

Comparative and case study researchers have responded to critiques of their methods by developing formal procedures to validate theoretical claims through set theoretical logics of causal conditions. This 'logico-formalist turn' has involved the stricter application of the schemas of set theory and the philosophy of logic to raise validation…

Even though agent-based modelling is seen as committing to a mechanistic, generative type of causation, the methodology allows for representing many other types of causal explanations. Agent-based models are capable of "integrating" diverse causal relationships into coherent causal mechanisms. They mirror the crucial, multi-level…

Context is a key concept in developing realist causal explanations but its conceptualisation has received comparatively less attention. We conducted a review to explore how context is conceptualised within realist reviews and evaluations. We purposively selected 40 studies to examine: How is context defined? And how is context operationalised in…

The capability approach has recently been recognised as a potential explanatory theory in disability research. However, to strengthen its explanatory power, it is argued that it should be grounded in a critical realist research paradigm. While critical realism is increasingly adopted in social inquiry, to date there remains little research that…

A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…

Single case studies can provide vital contributions to theory-testing in social science studies. Particularly, by applying the process-tracing method, case studies can test theoretical frameworks through a rigorous research design that ensures substantial empirical leverage. While most scholarly contributions on process-tracing focus on either…

We present three statistical methods for causal analysis in life course research that are able to take into account the order of events and their possible causal relationship: a cross-lagged model, a latent growth model (LGM), and a synthesis of the two, an autoregressive latent trajectories model (ALT). We apply them to a highly relevant…