How can regression-type studies, which try to get causal inferences by controlling for variables until whatever is left is plausibly a causal relationship, benefit as much as possible from qualitative research? This chapter offers three qualitative research designs that can help test and improve quantitative causal inferences based on control variables. First, we consider process-tracing designs that seek to discover previously unknown confounding variables that can be added as new control variables, thereby refining and improving the statistical model. Second, we discuss process tracing that seeks to confirm that control variables have a direct connection to the outcome variable, and therefore are relevant controls. Third, we discuss process tracing to check whether control variables might be posttreatment and therefore at least partially harmful. Finally, we provide a demonstration of the kind of iterated interaction that we have in mind between statistical efforts at causal inference and qualitative research to learn more about the assumptions behind the model, involving the relationship between labor union strength and the prevalence of employment law across U.S. states.

How can mixed-method research add value to experiments? There is much to learn by adding qualitative components to experiments that can test for problems related to measurement; networks and spillover among experimental subjects; issues related to the meaning of treatments, outcomes, and other aspects of the experiment for participants; the exhaustiveness of the intended causal content of the treatment; and moderation effects related to subgroups of participants, or to differences across implementations of an experiment in divergent contexts. Some of these areas relate to the goal of theoretical generalization from the initial experiment, but most of them also have connections with the meaning and quality of the causal inference for the experiment at hand.

This chapter summarizes key themes from the book as a whole and offers general concluding thoughts.

Process tracing methods, which involve ways of using information within a single case to think carefully about questions of social-science theory, have become one of the leading qualitative methods in political science and related fields. Can mixed-method approach to process tracing work without destroying the qualitative logic of the method? This chapter argues that two distinct forms of process tracing, involving testing of existing causal theories and discovery of new theories, each have room for mixed-method strategies. We show that qualitative components can become steps within a testing-based process tracing argument, and offer guidelines for structuring such studies. We then offer a novel approach to combining machine-learning techniques like LASSO regression with discovery-based process tracing, illustrating the design with an application to the rise in visibility of U.S. far right broadcaster Alex Jones.

How can quantitative methods support case studies in general? One common task in case-study research is presenting audiences with a large collection of texts. Text-as-data methods may facilitate this task by summarizing the overall collection more quickly and understandably than we can usually do ourselves, and by locating individual documents within the collection. We offer an application, showing how text-as-data methods effectively summarize the large collection of legal documents available regarding defendants in cases related to the January 6th invasion and facilitate case-study exploration and understanding of specific individuals. We also discuss how mixed-method approaches may save time and resources as a way of moving across levels of analysis within a case-study design. We wind up the chapter by raising a note of caution regarding common attempts to use statistics as a test of generalizability for case studies and regarding the somewhat less common but still recurrent designs that mix game theory and qualitative research. Both of these approaches can work, and can offer insights, but both are harder than they may initially appear.

Research designs can combine qualitative, quantitative, experimental, and data-science methods through careful planning, attention to details and assumptions, and methodological execution. This chapter introduces the book's perspective, arguing that designs that combine methods carefully and with close attention to their details will outperform designs where two or more methods are carried out in parallel and then compared. The chapter also considers a range of practical and philosophical questions related to whether it makes sense to combine methods. Is one method always best, such that it isn't worth trying? Do methods speak fundamentally different languages, such that there is no point? Are methods and problems inextricably linked, such that the question is irrelevant? We argue against each of these views.

This chapter builds a theory of local community protection from populist state violence, focusing on the “meso” level where state agents and communities interact. After describing the characteristics of this new type of political violence, it explains how two key variables – the moral commitment of local elites (Catholic priests and other religious actors) and the capacity of local social organizations (in this case, the Catholic parish) – facilitate community protection. Commitment and capacity have a path-dependent character, reflecting formative experiences for clergy, exposure to Catholic religious orders with histories of public action, and long church embeddedness in local communities. These two independent variables operate via six mechanisms: disrupting operations and reducing targets function through interactions with local state agents, threatening accountability and reintegrating victims involve partnerships with civil society, and raising moral salience and building solidarity work at the level of the local public.

This chapter describes the study’s research design. Protest event data from the three contexts over three decades, gathered with an intensive data collection strategy, was aggregated into a dataset of forty large far-right demonstration campaigns. The chapter describes the application of qualitative comparative analysis (QCA) and process-tracing techniques to detect patterns of causal conditions and then to evaluate rigorously the processual causation underlying those patterns. In social movement research and scholarship on the far right, single-case studies abound, providing rich qualitative depth but limited generalisability. At the same time, large-N quantitative research often lacks that depth of information that enables robust causal inferences. The main thrust of the research design applied here is overcoming these deficiencies.

Chapter 1 introduces the study’s core puzzle and overall logic of inquiry. It discusses main themes, locates arguments relative to relevant scholarship, and establishes the analytical framework. Early in the chapter, the puzzle of varying illiberal electoral outcomes is presented and contextualized. Captured by two distinct yet related indicators – illiberal voting and post-neoliberal populist magnitude – illiberal electoral outcomes not only varied persistently across countries but also signaled the high salience of economic issues in postcommunist Europe. The next section establishes the rationale for explaining outcomes by drawing insights from Latin America – another semi-peripheral space that experienced consequential neoliberal junctures. Having argued, based on key economic and political parallels between the two regions, that a critical juncture approach is appropriate also for making sense of developments in Eastern Europe, I spell out the work’s central propositions and highlight theoretical, methodological, and empirical contributions. The final sections discuss matters of research design and evidence – namely, the mixed method approach, case studies, and quantitative and qualitative data, including 100 interviews – as well as the book’s organization.

Quality data are necessary to test research questions about psychopathy. This chapter describes the research design of the Incarcerated Serious and Violent Young Offender Study (ISVYOS). The ISVYOS was initiated in 1998 and has been ongoing ever since. In this chapter I describe the ISVYOS that was used in the book, procedures for interviewing youth and collecting data in adulthood, control variables that were accounted for in the different analyses in this book, and the different measures of psychopathy that were available. This book focuses on 535 incarcerated youth who received an interview and rating on the PCL:YV. Many of these youth received psychopathy assessments using additional measures. To give readers a better sense of how psychopathy manifests in youth, I describe procedures for rating the PCL:YV and discuss and interpret different responses that youth provided that were used as indications of the presence of specific psychopathy traits. This includes describing manifestations of each item from the Interpersonal, Affective, and Lifestyle factors from the PCL:YV.

This chapter outlines the empirical strategy for studying policy triage, which occurs when limited administrative resources and growing policy stocks force agencies to prioritize certain implementation tasks over others. To measure policy triage, the analysis distinguishes between triage frequency and intensity. These dimensions together provide a nuanced assessment of overall implementation performance. The chapter also details the theoretical predictors of policy triage: whether central policymakers can shift blame for failures, whether implementing agencies can mobilize external resources, and whether they are internally committed to achieving policy goals despite resource constraints. To test these claims, the research design focuses on two policy areas — environmental and social policy — across six countries representing diverse administrative traditions. Data collection involves secondary document analysis and 157 expert interviews with implementation officials. By systematically capturing both formal and informal organizational practices, this methodology reveals the complex trade-offs inherent in modern public administration and underscores how different political and organizational conditions jointly shape policy triage.