---
title: "Case study"
chunk: 2/3
source: "https://en.wikipedia.org/wiki/Case_study"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:43:19.359633+00:00"
instance: "kb-cron"
---

Typical cases are cases that exemplify a stable cross-case relationship. These cases are representative of the larger population of cases, and the purpose of the study is to look within the case rather than compare it with other cases.
Diverse cases are cases that have variations on the relevant X and Y variables. Due to the range of variation on the relevant variables, these cases are representative of the full population of cases.
Extreme cases are cases that have an extreme value on the X or Y variable relative to other cases.
Deviant cases are cases that defy existing theories and common sense. They not only have extreme values on X or Y (like extreme cases) but defy existing knowledge about causal relations.
Influential cases are cases that are central to a model or theory (for example, Nazi Germany in theories of fascism and the far-right).
Most similar cases are cases that are similar on all the independent variables, except the one of interest to the researcher.
Most different cases are cases that are different on all the independent variables, except the one of interest to the researcher.
For theoretical discovery, Jason Seawright recommends using deviant cases or extreme cases that have an extreme value on the X variable.
Arend Lijphart, and Harry Eckstein identified five types of case study research designs (depending on the research objectives), Alexander George and Andrew Bennett added a sixth category:

Atheoretical (or configurative idiographic) case studies aim to describe a case very well, but not to contribute to a theory.
Interpretative (or disciplined configurative) case studies aim to use established theories to explain a specific case.
Hypothesis-generating (or heuristic) case studies aim to inductively identify new variables, hypotheses, causal mechanisms, and causal paths.
Theory testing case studies aim to assess the validity and scope conditions of existing theories.
Plausibility probes, aim to assess the plausibility of new hypotheses and theories.
Building block studies of types or subtypes, aim to identify common patterns across cases.
Aaron Rapport reformulated "least-likely" and "most-likely" case selection strategies into the "countervailing conditions" case selection strategy. The countervailing conditions case selection strategy has three components:

The chosen cases fall within the scope conditions of both the primary theory being tested and the competing alternative hypotheses.
For the theories being tested, the analyst must derive clearly stated expected outcomes.
In determining how difficult a test is, the analyst should identify the strength of countervailing conditions in the chosen cases.
In terms of case selection, Gary King, Robert Keohane, and Sidney Verba warn against "selecting on the dependent variable". They argue for example that researchers cannot make valid causal inferences about war outbreaks by only looking at instances where war did happen (the researcher should also look at cases where war did not happen). Scholars of qualitative methods have disputed this claim, however. They argue that selecting the dependent variable can be useful depending on the purposes of the research. Barbara Geddes shares their concerns with selecting the dependent variable (she argues that it cannot be used for theory testing purposes), but she argues that selecting on the dependent variable can be useful for theory creation and theory modification.
King, Keohane, and Verba argue that there is no methodological problem in selecting the explanatory variable, however. They do warn about multicollinearity (choosing two or more explanatory variables that perfectly correlate with each other).

== Uses ==
Case studies have commonly been seen as a fruitful way to come up with hypotheses and generate theories. Case studies are useful for understanding outliers or deviant cases. Classic examples of case studies that generated theories includes Darwin's theory of evolution (derived from his travels to the Galapagos Islands), and Douglass North's theories of economic development (derived from case studies of early developing states, such as England).
Case studies are also useful for formulating concepts, which are an important aspect of theory construction. The concepts used in qualitative research will tend to have higher conceptual validity than concepts used in quantitative research (due to conceptual stretching: the unintentional comparison of dissimilar cases). Case studies add descriptive richness, and can have greater internal validity than quantitative studies. Case studies are suited to explain outcomes in individual cases, which is something that quantitative methods are less equipped to do. Case studies have been characterized as useful to assess the plausibility of arguments that explain empirical regularities. By emphasizing context across cases, case studies can be useful in identifying scope conditions and evaluating to what extent concepts and theories apply across cases.
Through fine-grained knowledge and description, case studies can fully specify the causal mechanisms in a way that may be harder in a large-N study. In terms of identifying "causal mechanisms", some scholars distinguish between "weak" and "strong chains". Strong chains actively connect elements of the causal chain to produce an outcome whereas weak chains are just intervening variables.
Case studies of cases that defy existing theoretical expectations may contribute knowledge by delineating why the cases violate theoretical predictions and specifying the scope conditions of the theory. Case studies are useful in situations of causal complexity where there may be equifinality, complex interaction effects and path dependency. They may also be more appropriate for empirical verifications of strategic interactions in rationalist scholarship than quantitative methods. Case studies can identify necessary and insufficient conditions, as well as complex combinations of necessary and sufficient conditions. They argue that case studies may also be useful in identifying the scope conditions of a theory: whether variables are sufficient or necessary to bring about an outcome.
Qualitative research may be necessary to determine whether a treatment is as-if random or not. As a consequence, good quantitative observational research often entails a qualitative component.