This chapter describes case selection, which is a crucial component of designing social research. Its importance can hardly be overstated because the cases you choose affect the answers you get. However, how should researchers select their cases? A careful inspection of the research question, the study’s objective, should be the starting point. The research question typically anchors the study in a research area, specifies the universe of cases, and guides its engagement with theory. Ideally, case selection is solely driven by methodology; however, practicality and feasibility considerations frequently make adjustments to the design necessary. Such considerations concern, for instance, the costs of data collection. The chapter introduces a few commonly used case selection strategies as well as two hotly debated topics in the literature on case selection: selecting on the dependent variable and random case selection.
Laura Gelhaus and Dirk Leuffen
Paul Pennings and Hans Keman
This chapter examines the ‘art of comparing’ by showing how to relate a theoretically guided research question to a properly founded research answer by developing an adequate research design. It first considers the role of variables in comparative research, before discussing the meaning of ‘cases’ and case selection. It then looks at the ‘core’ of the comparative research method: the use of the logic of comparative inquiry to analyse the relationships between variables (representing theory), and the information contained in the cases (the data). Two logics are distinguished: Method of Difference and Method of Agreement. The chapter concludes with an assessment of some problems common to the use of comparative methods.
This chapter considers the main types of data used in Politics and International Relations, as well as the main criteria by which to judge whether the data collected is good or not. It first describes the steps involved in the process of thinking about what data or evidence is relevant to answering a research question before discussing the importance of addressing issues of validity and reliability in research. Some of these issues are illustrated by referring to recent attempts to measure corruption, a major topic of interest in Politics and International Relations. The chapter also examines the issue of case selection as well as the collection of qualitative and quantitative data using methods such as interviewing and observation. Finally, it analyses the so-called ‘big data’ revolution in data collection and analysis, and provides a data quality checklist.
Sample Types and Sample Size
Emilie van Haute
This chapter assesses sampling techniques. Researchers may restrict their data collection to a sample of a population for convenience or necessity if they lack the time and resources to collect data for the entire population. Therefore, a sample is any subset of units collected from a population. Research sampling techniques refer to case selection strategy — the process and methods used to select a subset of units from a population. While sampling techniques reduce the costs of data collection, they induce a loss in terms of comprehensiveness and accuracy, compared to working on the entire population. The data collected are subject to errors or bias. Two main decisions determine the size or margin of error and whether the results of a sample study can be generalized and applied to the entire population with accuracy: the choice of sample type and the sample size.
This chapter explores the principles of comparative research design as well as the issues and problems associated with different aspects of the approach. In particular, it considers the issue of case selection, the common sources of error that are associated with comparative research, and what can be done to try and avoid or minimize them. The comparative method is one of the most commonly used methods in political research and is often employed to investigate various political phenomena, including democratization, civil war, and public policy. The chapter discusses the three main forms of comparison, namely case study, small-N comparison, and large-N comparison. It also describes two main approaches used to select cases for small-N studies: Most Similar Systems Design and Most Different Systems Design. It also evaluates qualitative comparative analysis and concludes with an analysis of issues arising from case selection and data collection in large-N comparative research.