Editing Case study (section)

== Research design ==

As with other social science methods, no single research design dominates case study research. Case studies can use at least four types of designs. First, there may be a "no theory first" type of case [[study design]], which is closely connected to [[Kathleen M. Eisenhardt]]'s methodological work.<ref name="Ridder2017">{{cite journal|last=Ridder|first=Hans-Gerd|date=October 2017|title=The theory contribution of case study research designs|journal=Business Research|volume=10|issue=2|pages=281–305|doi=10.1007/s40685-017-0045-z|issn=2198-2627|doi-access=free|hdl=10419/177270|hdl-access=free}}</ref><ref name="Eisenhardt1991">{{cite journal |last=Eisenhardt |first=Kathleen M. |author-link=Kathleen M. Eisenhardt |title=Better Stories and Better Constructs: The Case for Rigor and Comparative Logic |journal=The Academy of Management Review |volume=16 |issue=3 |pages=620–627 |year=1991 |jstor=258921 |doi=10.5465/amr.1991.4279496 }}</ref> A second type of research design highlights the distinction between single- and multiple-case studies, following [[Robert K. Yin]]'s guidelines and extensive examples.<ref name="Ridder2017" /><ref name="Yin" /> A third design deals with a "social construction of reality", represented by the work of [[Robert E. Stake]].<ref name="Ridder2017" /><ref name="Stake1995">{{cite book |last=Stake |first=Robert E. |author-link=Robert E. Stake |title=The Art of Case Study Research |url={{GBurl|ApGdBx76b9kC|pg=PR99}} |pages=99–102 |year=1995 |publisher=SAGE Publications |location=Thousand Oaks, CA |isbn=978-0-8039-5767-1}}</ref> Finally, the design rationale for a case study may be to identify "anomalies". A representative scholar of this design is [[Michael Burawoy]].<ref name="Ridder2017" /><ref name="Burawoy2009">{{cite book |last=Burawoy |first=Michael |author-link=Michael Burawoy |title=The Extended Case Method: Four Countries, Four Decades, Four Great Transformations, and One Theoretical Tradition |url={{GBurl|xCA7R-o8BMIC}} |year=2009 |publisher=University of California Press |location=Berkeley |isbn=978-0-520-94338-4 }}</ref> Each of these four designs may lead to different applications, and understanding their sometimes unique [[ontology|ontological]] and [[epistemology|epistemological]] assumptions becomes important. However, although the designs can have substantial methodological differences, the designs also can be used in explicitly acknowledged combinations with each other.

While case studies can be intended to provide bounded explanations of single cases or phenomena, they are often intended to raise theoretical insights about the features of a broader population.<ref name=":2" />

=== Case selection and structure ===

Case selection in case study research is generally intended to find cases that are representative samples and which have variations on the dimensions of theoretical interest.<ref name=":2" /> Using that is solely representative, such as an average or typical case is often not the richest in information. In clarifying lines of history and causation it is more useful to select subjects that offer an interesting, unusual, or particularly revealing set of circumstances. A case selection that is based on representativeness will seldom be able to produce these kinds of insights.

While a random selection of cases is a valid case selection strategy in [[Big data|large-N]] research, there is a consensus among scholars that it risks generating serious biases in small-N research.<ref name=":6" /><ref name=":3" /><ref name=":2" /><ref name=":18">{{Cite book|last=Gerring|first=John|url=https://books.google.com/books?id=xECY0nnkTvMC|title=Case Study Research: Principles and Practices|date=2007|publisher=Cambridge University Press|isbn=978-0-521-85928-8|pages=87|language=en|quote=Random sampling is unreliable in small-N research}}</ref> Random selection of cases may produce unrepresentative cases, as well as uninformative cases.<ref name=":18" /> Cases should generally be chosen that have a high expected information gain.<ref name=":7" /><ref name=":2" /><ref name=":9">{{Citation|last=Seawright|first=Jason|title=Case Selection after Regression|date=2016|url=https://www.cambridge.org/core/books/multimethod-social-science/case-selection-after-regression/5A581A473A1D9ADBFA98A5DE607B4DA4|work=Multi-Method Social Science: Combining Qualitative and Quantitative Tools|volume=|pages=75–106|publisher=Cambridge University Press|doi=10.1017/cbo9781316160831.004|isbn=978-1-107-09771-1|access-date=2021-02-11|url-access=subscription}}</ref> For example, [[outlier]] cases (those which are extreme, deviant or atypical) can reveal more information than the potentially representative case.<ref name=":9" /><ref name="Huang2015">{{cite book |last1=Huang |first1=Huayi |year=2015 |title=Development of New Methods to Support Systemic Incident Analysis |type=Doctoral dissertation |publisher=Queen Mary University |location=London |url=https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/12866/Huang_Huayi_PhD_Final_111115.pdf }}{{page needed|date=December 2017}}</ref><ref name="Underwood2016">{{cite journal |doi=10.1016/j.ssci.2015.08.014 |title='Accident investigation in the wild' – A small-scale, field-based evaluation of the STAMP method for accident analysis |journal=[[Safety Science]] |volume=82 |pages=129–43 |year=2016 |last1=Underwood |first1=Peter |last2=Waterson |first2=Patrick |last3=Braithwaite |first3=Graham }}</ref> A case may also be chosen because of the inherent interest of the case or the circumstances surrounding it. Alternatively, it may be chosen because of researchers' in-depth local knowledge; where researchers have this local knowledge they are in a position to "soak and poke" as [[Richard Fenno]] put it,<ref name=" Fenno2014">{{cite journal |last=Fenno |first=Richard F. |author-link=Richard Fenno |title=Observation, Context, and Sequence in the Study of Politics |journal=American Political Science Review |volume=80 |issue=1 |pages=3–15 |year=2014 |doi=10.2307/1957081 |jstor=1957081 |s2cid=145630377 }}</ref> and thereby to offer reasoned lines of explanation based on this rich knowledge of setting and circumstances.

Beyond decisions about case selection and the subject and object of the study, decisions need to be made about the purpose, approach, and process of the case study. [[Gary Thomas (academic)|Gary Thomas]] thus proposes a typology for the case study wherein purposes are first identified (evaluative or exploratory), then approaches are delineated (theory-testing, theory-building, or illustrative), then processes are decided upon, with a principal choice being between whether the study is to be single or multiple, and choices also about whether the study is to be retrospective, snapshot or diachronic, and whether it is nested, parallel or sequential.<ref name="Thomas">{{cite journal |doi=10.1177/1077800411409884 |title=A Typology for the Case Study in Social Science Following a Review of Definition, Discourse, and Structure |journal=Qualitative Inquiry |volume=17 |issue=6 |pages=511–21 |year=2011 |last=Thomas |first=Gary |s2cid=144895919 |author-link=Gary Thomas (academic) |url=https://zenodo.org/record/894078 }}</ref>

In a 2015 article, John Gerring and Jason Seawright list seven case selection strategies:<ref name=":2">{{Citation|last1=Seawright|first1=Jason|title=Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options|work=Political Research Quarterly|volume=|pages=|year=2014|doi=10.4135/9781473915480.n31|isbn=978-1-4462-7448-4|last2=Gerring|first2=John}}</ref>

# 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.<ref name=":9" />

[[Arend Lijphart]], and [[Harry H. Eckstein|Harry Eckstein]] identified five types of case study research designs (depending on the research objectives), Alexander George and Andrew Bennett added a sixth category:<ref>{{Cite book|last1=George|first1=Alexander L.|title=Case Studies and Theory Development in the Social Sciences|last2=Bennett|first2=Andrew|date=2005|publisher=MIT Press|isbn=978-0-262-30307-1|pages=74–76, 213|oclc=944521872}}</ref>

# 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:<ref>{{Cite journal|last=Rapport|first=Aaron|date=2015|title=Hard Thinking about Hard and Easy Cases in Security Studies|url=http://www.tandfonline.com/doi/full/10.1080/09636412.2015.1070615|journal=Security Studies|language=en|volume=24|issue=3|pages=431–465|doi=10.1080/09636412.2015.1070615|s2cid=131769695|issn=0963-6412}}</ref>

# 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 (political scientist)|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).<ref name=":3" /> 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.<ref name=":7" /><ref name=":8" /><ref name=":10" /> 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.<ref name=":0" />

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).<ref name=":3">King, Gary/ Keohane, Robert O./ Verba, Sidney: ''Designing Social Inquiry. Scientific Inference in Qualitative Research''. Princeton University Press, 1994.</ref>