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• Extended Case Method
• Theoretical Sampling
• Multi-Sited Ethnography
• Triangulation
• Snowball Sampling

Comparative Case Studies

• Agent Based Models
• Qualitative Longitudinal Research
• Gatekeepers in Ethnography
• Gatekeepers in Qualitative Research

Discover method in the Methods Map

• By: Delwyn Goodrick | Edited by: Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A.Williams
• Publisher: SAGE Publications Ltd
• Publication year: 2019
• Online pub date: September 17, 2019
• Discipline: Anthropology , Business and Management , Communication and Media Studies , Computer Science , Counseling and Psychotherapy , Criminology and Criminal Justice , Economics , Education , Engineering , Geography , Health , History , Marketing , Mathematics , Medicine , Nursing , Political Science and International Relations , Psychology , Social Policy and Public Policy , Science , Social Work , Sociology , Technology
• Methods: Case study research , Comparative research , Experimental design
• Length: 5k+ Words
• DOI: https:// doi. org/10.4135/9781526421036849021
• Online ISBN: 9781529748338 More information Less information
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The comparative case study approach is a powerful design to generate causal explanations, and as such, it is well suited for answering “how” and “why” research questions. It privileges deep knowledge of cases or entities. Comparative case studies involve iterative phases of theory identification, case selection, data gathering, and comparative analysis, within and between cases. They can be adopted as the primary design framework in a research study or may be embedded within another design. For example, a researcher may include case studies within a broader mixed methods or experimental study to highlight causal mechanisms and to add richness and detail to research claims.

Comparative case studies are a defined type of case study. While comparative case studies share much in common with other case study approaches, a key differentiating feature is their focus on generating explanatory claims and the requirement for theory and evidence-informed case selection. The researcher explores and examines two or more cases to construct causal propositions or inferences about social phenomena. The researcher then selects subsequent cases to test and modify these propositions. This entry outlines key features of comparative case studies and provides an overview of key considerations in selecting this design for social research and program evaluation.

Causality in Social Research

Researchers interested in causal analysis will be attracted to the potential of comparative case studies. Traditionally, experimental designs have been privileged as the gold standard for causal explanation. The comparative case study design provides a compelling alternative to the experiment, as it supports a nuanced understanding of how and why observed patterns have been produced.

There is a good fit between the assumptions of realism and the use of comparative case studies. Most forms of realism claim that social knowledge is nonlinear, adaptive, and context-dependent. To understand causes in diverse social contexts, there is a need to understand how and in what ways mechanisms have “fired,” and how these mechanisms have been responded to by social actors within those contexts. Here context is understood as more than geographic setting but inclusive of sociocultural dimensions, politics, values, and social relationships.

An intervention, such as a reading program in schools, may produce differential outcomes for students in a range of schools. Researchers seek to understand why it worked in some cases and not others. They cannot manipulate or control the conditions or the students’ responses, but they want to better address the analytic puzzle to explain the reasons for differential outcomes.

Some social contexts demand a combination of research conditions or mechanisms to produce outcomes. The existence of the aforementioned reading program may not have, on its own, produced outcomes. Rather, it may be that it was a combination of the reading program, student engagement, and teaching quality that contributed to improved reading ability among students. In this scenario, the comparative case study researcher is interested in understanding the causal recipe or causal packages that influenced achievement of intended outcomes. To distinguish this type of causal reasoning from traditional conceptions of causality, the term case causality or generative causality may be a helpful qualifier.

The comparative case approach encourages researchers to examine cases in sufficient depth to understand the potential causal mechanisms, to describe context, and to explain complex patterns. To achieve this, the study will draw on qualitative and quantitative methods and incorporate systematic comparative analyses.

Like most research designs in the social sciences, paradigmatic commitments and disciplinary orientation influence the way that comparative case studies are conceptualised and practiced. Some empiricist researchers may reject the potential of any design outside the experimental design to generate and test causal claims, limiting the value of case studies to description or interpretation. Constructivist or post-structuralist scholars may challenge the value, feasibility, or appropriateness of causal analysis within the social sciences. While characterisations of comparative case studies reflect diverse perspectives, a moderate realist stance underpins much of the guidance offered in the literature.

Definitional Issues

There is considerable diversity in the way case study designs are described and defined within the literature. While this can be confusing to researchers new to case study, it is no different from the potential for confusion that surrounds other research designs. For example, quasi-experimental design is an umbrella term that incorporates several subtypes, including time series, pretest posttest, and nonequivalent groups design with either independent or repeated measures. Similarly, case study is the umbrella term, with varying subtypes, such as single or intrinsic case study, comparative case study, and descriptive case study.

Classifications are helpful, as they assist researchers to select approaches that address their research objectives. However, discussions of comparative case studies in the literature, like other types of case study, are marked by inconsistency in terminology, contradictory or conflicting guidelines, and differing perspectives on their scope. Case studies are variously associated with their purpose (e.g., as descriptive or explanatory), with the methods of data collection used (e.g., as qualitative or mixed method), or as a strategy for presenting reports (e.g., a case study report). The array of definitions of case study in the literature and conflation of terms limits the scholarly spread of case study approaches and contributes to a “curious methodological limbo” (Gerring, 2004, p. 341).

These differences in characterisation of case study extend to comparative case studies. The design considerations and use of case study approaches differ within and across disciplines, and according to the epistemological stance of key authors. For example, Robert Yin (1984/2014), writing about case studies in the social sciences, orients his approach to case studies from a moderate realist position, maintaining concern for the “holy trinity” (Kvale, 1994) of internal and external validity, and reliability. Robert Stake (1995) adopts a social constructionist perspective emphasising the value of impressionistic interpretation, trustworthiness, and thick description in collective and multiple case studies. Alexander George and Andrew Bennett (2005) highlight multimethod analytic techniques that may be useful for comparative case studies in comparative politics and international relations from a neopositivist perspective. More recently, Lesley Bartlett and Frances Vavrus (2017) pointed to the value of sociocultural and processual approaches to comparative case studies in policy studies using predominantly interpretive qualitative methods. These different stances necessarily shape researchers’ understanding of the purpose, design, and analytic techniques best suited to case study, and by extension to comparative case study. While this section has identified differences in approaches, these scholars do share a commitment to structured comparison within and among cases, and case-based knowledge.

The Role of Comparison

Comparative case studies involve explicit, formal, and structured focus on comparison to produce causal inferences about social phenomena. Comparison indicates that the researcher is systematically examining similarities and differences within and among cases. The goal, however, is to compare to generate an understanding of the way patterns and configurations of cases work. This contributes to differentiating the cases (Ragin & Amoroso, 2019).

While there is some level of comparison in all case studies—even single case study (which draw on comparison with a wider class of events outside the study)—in many case study approaches, comparison is used to inform case description, illuminate social processes, or showcase complexity. Comparison is not used for explanatory purposes, and methods that facilitate comparative analysis may therefore not be used. While a thick, descriptive account may be valuable in illuminating social processes, a collective or multiple case study may not be appropriately classified as a comparative case study.

The popular adage in social research “correlation is not causation” has a fitting analogy in comparative case study: “Comparison does not make a case study comparative.” For many program or policy evaluators, the focus on a case—for example, implementation success or outcomes from implementation of a new information and communication technology (ICT) initiative in schools—may lead to a simplistic assessment that the study is a comparative case study design. The case involves assessment of implementation of ICT initiatives, and the schools that have implemented the new initiative are identified as sites to study implementation. The study may be focused on describing the use of ICT in schools using mixed methods or conceptualised as a collective case study where similarities and differences within and across cases are examined. However, it is not necessarily a comparative case study, as it may not include theoretically informed case selection, and may not utilise analytic techniques that enable explanatory claims to be made about causal conditions within and across cases. In this sense, adopting the term comparative case study as a label for the study is inappropriate. The design is used as a label, as a “methodological blanket” (Bartlett & Varvrus, 2017), rather than as an explicit framework that guides researchers in how they conceptualise, conduct, and report their research.

Central Features of Comparative Case Studies

This section highlights core features of comparative case studies. The purpose of the presentation is to differentiate comparative case studies from other types of case study. There are four key characteristics of comparative case studies:

• 1. A focus on causal explanation
• 2. Theory-guided case selection
• 3. Iterative use of qualitative and quantitative methods
• 4. Case-based knowledge.

A Focus on Causal Explanation

Researchers who adopt comparative case studies seek to generate causal explanations about social or historical contexts. This means they will necessarily need to address issues of causal complexity, as there is unlikely to be a single explanation or explanatory condition for observed outcomes (Ragin, 1987). A key task is to explore how patterns or configurations of conditions are linked to different outcomes. This requires careful and systematic definition of the outcome, and thorough knowledge of the contexts in which these outcomes have or have not occurred. It also requires understanding of conditions that may produce these outcomes.

Traditional approaches to causal analysis (e.g., forms of regression analysis) are variable rather than case oriented. The data set often consists of a large number of cases and a limited number of variables to be examined. The level of each variable is compared with the outcome variable in an additive manner. During the process, conditions or variables that are weak may be discarded to generate a parsimonious explanation of causal effects.

While assessing cause and effect in this way is useful, it does not help researchers understand how and why an intervention worked or did not work. Such approaches are not well suited to address complexities in social life and do not account for the existence of multiple conditions or independent variables that may combine in different ways to produce an outcome (known as equifinality). For example, a researcher may be interested in understanding how and why a student well-being program worked well within a particular region and did not work so well in others. While the program may have been implemented with fidelity to the overarching model, it is likely that elements of the school context (teachers, sociodemographic characteristics of schools, school governance and leadership) and students’ responses (level of motivation and interest, perceived program relevance) may have influenced the outcomes achieved. A feasible research strategy may be to report differential outcomes by school and associate these outcomes with patterns of implementation, but a more relevant analysis for a policy audience may be to explain the reasons for the similar and different outcomes.

Selection of several schools with similar and different patterns of outcomes may generate propositions about the core mechanisms in operation within and across these diverse environments. From a policy perspective, this is valuable information for improving policy implementation and for increasing knowledge about what is required to achieve outcomes.

The analytic processes used in comparative case studies are based on an appreciation that there is no straightforward, linear relationship between causes and outcomes. Similar processes can lead to different outcomes in different contexts. And seemingly distinct processes may lead to similar outcomes. Identifying presence or absence of conditions or outcomes is not adequate. The researcher seeks to understand and explain patterns and establish plausible explanations for why they have occurred. The comparative task is to question and explore configurations across cases, not to merely compare them in a static way.

Most analytic techniques used in comparative case studies combine some element of process tracing (reconstructing the causal sequence of conditions and linking these to outcomes) and narrative explanation. Alternative explanations for outcome patterns are sought, and rival (or competing) explanations are systematically identified and ideally eliminated. A replication logic (Yin, 2014) underpins many of these analytic techniques, as patterns are examined across cases and tested in subsequent cases, but some (e.g., qualitative comparative analysis [QCA], some forms of process tracing and most different cases/similar outcome; most similar cases/different outcome [MDSO; MSDO]) require strong quantitative skills, while others (e.g., horizontal, vertical, and transversal comparison; narrative comparison) require strong qualitative skills.

Table 1 provides an outline of the most common analytic strategies. These are analytic options, not prescriptions for analysis. Analysis is an intellectual and conceptual activity, not merely a technical one. There are a range of techniques developed to support causal comparison in case-based studies, but they should not be uncritically applied.

Techniques may be usefully combined; however, methods are underpinned by different principles, with specific technical requirements, which may make integration challenging. The reader interested in comparative case studies should select the analytic methods most suited to his or her research objectives, cases, and the required knowledge and skill set.

Theory-Led Case Selection and Iteration

A second key feature of comparative case studies is concerned with case selection. As the purpose of comparative case studies is to generate explanatory claims through recursive examination of cases, the researcher needs to provide a clear rationale for inclusion and exclusion of cases within the study.

Cases in comparative case studies are cases of something. For example, in an evaluation of the impact of an ICT intervention in primary schools, schools are selected because they will shed light on reasons the intervention was successful or not successful. The school is the entity selected, but it is only of interest as a case because it will enable the researcher to examine the topic of interest (i.e., impact of ICT). There are scope conditions and boundaries that structure decisions about selection of the case. Charles Ragin famously suggested the need to clearly identify, “What is this a case of?” (Ragin & Becker, 1992), recognising that this may shift over the course of the study. Gary Thomas (2011) refers to the importance of clarifying the subject and object of study. The subject in this example is the school selected, and the object is the impact of the ICT intervention.

Initial case selection is guided by analytic interest or theory. Provisional explanations may be formed, and then other cases selected to build, elaborate, or test theory emerging from the study. Selection of cases and case comparisons are iterative, not opportunistic or probabilistic. This means that case selection and conditions for case comparison cannot often be fully specified at the beginning of a study.

As researchers gather evidence, they generate conjectures and propositions. These are then systematically tested with subsequent evidence and subsequent cases and refuted or incorporated into the explanation. Researchers using comparative case studies can select a number of different cases with similar outcomes or similar types of cases with different outcomes to trace the causal pathway and identify the causal recipe (Ragin, 2008).

There are a range of ways that cases can be selected, and case selection will depend on research goals and budget and time considerations. In large N comparative case studies, a purposeful random selection of cases that share criteria may be adopted. However, in small N studies, like most comparative case studies, random selection may be problematic. Other case selection techniques that may be considered include the extreme case, the deviant case, and the local knowledge or exemplary case.

In practical terms, researchers choose cases that will provide the strongest possible test of theories. Deviant cases may be of interest in generating new propositions or identify other conditions that were left out of the initial specification. For example, the researcher interested in explaining the way that a school leadership program influenced school outcomes may elect to examine a case where causal conditions were present (attendance and completion of a school leadership program), but exploring where the expected outcome did not occur would be useful in highlighting the influence of other conditions. Alternatively, selecting a case (a school) that has good school outcomes but did not have the program in place could be useful in identifying additional conditions or new causal conditions that contributed to school outcomes.

Mixed Methods of Data Collection

The researcher undertaking comparative case studies needs to be methodologically dexterous in applying a range of techniques, including surveys and secondary data analysis (quantitative) and interviews, observations, and focus group discussions (qualitative) as appropriate in the study. Qualitative and quantitative data collection techniques are drawn on to support case-based understanding and to facilitate comparative analyses.

Depending on the scope, availability, and quality of data, the researcher may give more “weight” to particular sets of data than others. These decisions should be made explicit in construction of the reports. Janice Morse and Linda Niehaus (2009) developed useful notation rules to encourage researchers to be explicit about their decision rules for prioritising evidence derived from adopting both qualitative and quantitative approaches in a study. These notations that reflect weighting of components and sequencing of methods may be instructive for researchers using comparative case studies and facilitate methodological transparency. They argued that most studies have an inductive or deductive drive and, while these may overlap, it is useful to identify which is dominant at stages within any given study. In historical comparative studies, the role of retroduction and abduction could also be considered.

The use of mixed methods (qualitative and quantitative) or multiple methods (interviews, observations, and document analysis) within a methodology may strengthen claims by balancing the potential weaknesses of mono-method studies. Triangulation relates to strategies to overcome the potential weaknesses that can arise from the use of a single method, single data source, single observer, and/or single theoretical base.

While there are four types of triangulation, the research selects those most relevant to the study to test and refine propositions. Triangulation in this sense is not just about seeking convergence but addressing the reasons for divergent findings as well. The researcher does not merely focus on the technical aspects of method, although these are important but makes thoughtful inquiries into converging and diverging patterns.

Case-Based Knowledge

All research is in some way about cases. Researchers who use comparative case studies recognise the importance of understanding cases within their contexts to make plausible causal claims. The focus is on the cases and understanding the cases rather than focusing on the variables or conditions that make up the case. Being case oriented means that the researcher is interested in the complex interactions of conditions through an intensive focus on a limited number of cases.

There are inevitable trade-offs between breadth and depth. Comparative case study researchers must balance theoretical sharpness and explanatory strength with practical considerations about the number of cases that can be examined. One exception is worth noting. In large N case studies (up to 200), it is likely that the researcher will not have deep case-based knowledge. There are limits in the researcher’s capacity to explore context and gain an in-depth understanding, especially with a growing number of cases, and the researcher may also experience difficulties in his or her capacity to address and consider multiple conditions across cases under study. It is likely that this will influence options for comparative analysis; in large N studies, the use of narrative comparisons or causal narratives will be limited.

An Illustrative Example

The following scenario provides a concise example of the strategies that researchers may consider when designing a comparative case study. The example relates to an evaluation study commissioned by a government agency in Australia.

The agency commissioned an evaluation to assess the impact of an ICT program in 40 schools across two municipalities. The policy audience was interested in finding out how the initiative was implemented and what difference the initiative made to students’ skills in using ICT, their engagement in the classroom, and their capacity for problem-solving.

A working theory (developed from program theory and logic mapping) was proposed that one of the causal mechanisms underpinning the success of the ICT initiative was the level of student confidence. It was argued that students that experience success with their ICT project and enjoy undertaking the project will feel more confident in using ICT and better engage in classroom learning.

The evaluator needs to understand how the program was implemented and to what extent intended outcomes occurred. The evaluator may also be interested in understanding positive and negative unintended outcomes of the intervention (such as the impact of the ICT initiative on teachers’ confidence). But, the evaluator is also interested in examining the mechanisms through which these outcomes have occurred, understanding that there are likely to be multiple causal pathways, not just one.

The comparative case study is separated into phases. In the first phase, the evaluator obtains background information about the ICT program and the rationale for the program, contextual information about the two municipalities, and gathers information from schools implementing the initiative. Data collection includes a school survey, student attendance data, and implementation interviews with the key teachers and the ICT program manager. This initial scoping generates data about the characteristics of schools involved in the ICT initiative (including sociocultural and demographic elements, teacher experience, and previous inclusion of ICT within the curriculum).

In Phase 2, the evaluator analyses the initial data collected and looks for patterns—similarities and differences in implementation and in outcomes across schools. Propositions are developed about conditions (confidence and any other conditions identified from Phase 1 data gathering) that seem to be associated with the desired outcome (student skills in ICT, student engagement). In Phase 3, the evaluator may choose to purposively select cases on the following basis:

• Selection of cases (schools and students) where students had low levels of confidence but achieved high levels of engagement in the classroom and skills in ICT;
• Selection of cases (schools and students) where outcomes were achieved but with diverse levels of implementation of the program;
• Selection of cases where students exhibited high levels of confidence but did not achieve anticipated outcomes.

Case selection strategies in this context may overlap as there may be clusters of causal conditions that were sufficient to produce the outcomes without the ICT intervention.

This design will require further data collection, which may include interviews with students and teachers within the selected schools, focus group discussions (with program implementers), and review of secondary data. Other select schools can then be included to examine similarities and differences in responses of students, teachers, and experts to the program, and their influence on outcomes. The brief example illustrates the design considerations that comparative case study researchers may need to consider, and the importance of conceptual, technical, and methodological skills.

Guidelines for Designing Comparative Case Studies

While the discussions of comparative case studies share the purpose of generating explanatory claims and a focus on causal inference, researchers differ in their presentation of the core requirements for comparative case study design, strategies of case selection, and analysis requirements. A key challenge for the use of comparative case studies is that the application of these techniques has often not been explained well, and the logic underpinning comparative analysis has not been well articulated. The following series of guidelines for effective comparative case studies are offered for heuristic purposes to encourage transparency.

1. Describe the Purpose of the Comparative Case Study and Determine the Types of Entities That Will Be Studied

The researcher will need to clarify the objective of the comparative case study, the topic of focus, and the rationale for case selection. It may be that this initial conception of the case and parameters for case selection will shift over time, but initial mapping will ensure that design decisions clearly follow intent.

2. Identify Positionality and Orientation to Comparative Case Studies

There are a range of ways that comparative case studies can be designed and conducted. Many of the differences in the literature reflect different disciplinary traditions and paradigmatic stances. A comparative case study undertaken from a realist position (e.g., George & Bennett, 2005) using process tracing and QCA is likely to be very different from a comparative case study undertaken using interpretive analytic techniques (e.g., Bartlett & Vavrus, 2017). The meaning of comparative case studies needs to be made explicit within parameters of disciplinary approach, assumptions, and methods. Researchers must make their approach to comparative case studies explicit so that reviewers and readers are able to assess the alignment with approaches documented in the literature.

3. Construct a Design Diagram

As comparative case studies often incorporate multistage sampling and diachronic data collection and analysis processes (Thomas, 2015), reliance on a narrative description of the design may be inadequate. It may be helpful to construct a diagram that depicts the elements of the design, including the context in which the cases are situated, the cases themselves, case selection strategies, and the methods of data collection and analysis. A diagram can assist readers in making sense of the comparative case study design and assist them in critical assessment of it.

A comparative case study research plan may also include a matrix or table of the characteristics/features of each case with relevant conditions to be explored, elaborated, or tested to demonstrate the way in which theory informed initial specifications, case selection, and analysis. Reviewers need to assess the relevance of case selection to analytic questions.

4. Identify Methods That Will Address Research Objectives and Generate a Depth Understanding of the Cases

Decisions about methods will necessarily be balanced with practical decisions including availability of data, access, time frame, and budget. In historical comparative case studies, primary data collection may not be possible, and the researcher will rely on secondary data. In most situations for causal analysis, case selection will evolve based on findings and propositions from fieldwork. Variations in application of methods across cases should be documented and propositions linked to subsequent case selection. This documentation will assist in maintaining an audit trail (Lincoln & Guba, 1985) of design, method, and analysis decisions.

5. Be Explicit and Transparent About Within-Case and Cross-Case Data Analysis Processes Used to Generate and Test Propositions

Analytic choices in comparative case studies will include a combination of within-case and cross-case analysis. While a range of techniques exist to support causal reasoning, simplistic application of these techniques may not be sufficient. Alexander George developed the method of structured focused case comparisons to encourage rigour, transparency, and to support some level of standardisation in the process. The concern for rigour is shared by Yin (2014) who recommends the development of a case study protocol to guide decisions about the study. In structured focused comparison, the researcher creates a set of general questions that relate to the research objectives and specifies the cases to structure initial data collection and analytic frame to ensure relevance.

6. Address Trustworthiness and Transferability of Claims

Given the array of approaches to social research, it is important that researchers adopting comparative case studies address potential criticisms. Comparative case studies have been criticised for inadequate specification of the limits of generalisability arising from case selection. Generalisability is synonymous with external validity. Criticisms of the limits of generalisability of comparative case studies appear to be associated with an empiricist conception of the term generalisability .

Traditionally, generalisability relies on representativeness of a sample to the population and a sufficiently large sample to enable sufficiency tests of generalisability. As comparative case studies are theory informed and the cases are purposively selected to build, test, elaborate, or refute theory, probabilistic generalisation may be less relevant. Indeed, probabilistic generalisation is only one form of generalisation. In comparative case studies, two alternative conceptions of generalisation can be identified.

Yin’s (2014) concept of analytic generalisation in case study aligns with the commitment to limit conclusions to the class of events under study, which is similar to contingent or limited generalisation. Generalisations are at the level of theory rather than at the level of the relationship between sample and population.

In interpretively oriented case studies, the concept of naturalistic generalisation coined by Stake (1995) may also provide useful guidance to the comparative case studies researcher. Naturalistic generalisation occurs when the reader translates the evidence presented in the case study to his or her own context. The rich description inherent in many case studies provides the opportunity for the reader to apply claims to wider contexts with which he or she is familiar.

Good comparative analysis requires systematic procedures, conceptual insight, questioning, iteration, and practical wisdom. Donald Campbell (1984) pointed to the need for researchers to welcome being part of a disputatious community. Researchers need to make rigorous, defensible claims, while being open to challenge from other scholars and the wider community. Comparative case studies offer researchers guidance on how to balance depth with breadth to generate plausible causal claims.

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Qualitative Comparative Analysis (QCA): A Classic Mixed Method Using Theory

• First Online: 29 July 2022

Cite this chapter

• Wendy Olsen 2  

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Qualitative comparative analysis (QCA) is an umbrella set of methods that use case-study evidence. This chapter begins by describing a case-study research example. The table-making stage is followed by a table-reduction stage. These two stages are similar to or analogous to standard survey data methods. Thus similarities with regression are noted.

This chapter then covers the original scaling, the fuzzy-set membership score, and a Z-score transformation for fuzzy sets. Crisp sets are simple binaries, such as zero/one, while fuzzy sets range from 0 to 1, but both measure the degree of set-membership as a property of an entity. For groups of cases (i.e. of these entities), each permutation of variables and/or contextual conditions is distinct. Multiple similar cases are grouped, and are then known as a configuration.

This chapter defines sufficient cause using a Boolean approach. A dependent variable can be found to occur if-and-only-if some conditions exist (sometimes written iff), but ‘if-and-only-if’ is not the same as sufficient cause. ‘If-and-only-if’ implies that the independent variables are both necessary and sufficient for the outcome. QCA teases these out as different relations (one is a subset and the other is a superset relation). By contrast, regression models require that causes be both necessary and sufficient for the dependent variable, and under that strong definition of causality, the modeller often resists commenting on causal mechanisms at all. In this chapter QCA is offered as a way to address confirmatory causal models directly using empirical evidence, both qualitative and quantitative. A complementary method is to offer an F test of each of the QCA results.

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Olsen, W. (2022). Qualitative Comparative Analysis (QCA): A Classic Mixed Method Using Theory. In: Systematic Mixed-Methods Research for Social Scientists. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-93148-3_6

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Article contents

Comparative case study research.

• Lesley Bartlett Lesley Bartlett University of Wisconsin–Madison
• , and  Frances Vavrus Frances Vavrus University of Minnesota
• https://doi.org/10.1093/acrefore/9780190264093.013.343
• Published online: 26 March 2019

Case studies in the field of education often eschew comparison. However, when scholars forego comparison, they are missing an important opportunity to bolster case studies’ theoretical generalizability. Scholars must examine how disparate epistemologies lead to distinct kinds of qualitative research and different notions of comparison. Expanded notions of comparison include not only the usual logic of contrast or juxtaposition but also a logic of tracing, in order to embrace approaches to comparison that are coherent with critical, constructivist, and interpretive qualitative traditions. Finally, comparative case study researchers consider three axes of comparison : the vertical, which pays attention across levels or scales, from the local through the regional, state, federal, and global; the horizontal, which examines how similar phenomena or policies unfold in distinct locations that are socially produced; and the transversal, which compares over time.

• comparative case studies
• case study research
• comparative case study approach
• epistemology

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