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This chapter differentiates between grand theory and middle-range theory. The study of social phenomena raises the twofold question about the internal and external validity of a hypothesis. A piece of research is internally valid when it describes the true state of affairs within its own setting. The extent to which its findings can be applied to other settings will determine its relative external validity. External validity is a product of the theoretical aspirations of the research. When grand in scope, theoretical aspirations reject the importance of specific variations and attempt to describe the true state of affairs in all settings. Conversely, a theory-building exercise with a mid-range scope is bound by a set of conditional statements. Whereas middle-range theory-building is rooted in generalizable empirical propositions, grand theory-building is based on internally consistent ontologies. On the one hand, grand theory favours highly abstract theorizing, which is fairly distinct from concrete empirical concerns. On the other hand, middle-range theories reflect more sociologically embedded theorizing, which strives to integrate theory and empirical variations over time and space.

This chapter explores the principles of experimental research design as well as the issues and problems associated with different aspects of the approach. In particular, it considers the issue of internal and external validity, the common obstacles associated with experimental research, and what can be done to try and avoid or minimize them. The chapter first describes the five steps involved in the classic version of the experimental design before discussing three types of experimental design: laboratory experiments, field experiments, and natural experiments. It also examines the ethical issues that arise from experimental research and concludes by highlighting some of the advantages of experimental research.

This chapter highlights statistical significance. The key question in quantitative analysis is whether a pattern observed in a sample also holds for the population from which the sample was drawn. A positive answer to this question implies that the result is ‘statistically significant’ — i.e. it was not produced by a random variation from sample to sample, but, instead, reflects the pattern that exists in the population. The null hypothesis statistical test (NHST) has been a widely used approach for testing whether inference from a sample to the population is valid. Seeking to test whether valid inferences about the population could be made based on the results from a single sample, a researcher should consider a wide variety of approaches and take into the account not only p-values, but also sampling process, sample size, the quality of measurement, and other factors that may influence the reliability of estimates.

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.

This chapter focuses on the basic principles of research design. It first considers different types of research design, including experimental designs, cross-sectional and longitudinal designs, comparative designs, and historical research designs. It also discusses two types of research validity: internal validity and external validity. The chapter proceeds by describing various methods of data collection and the sort of data or evidence each provides, including questionnaires and surveys, interviewing and focus groups, ethnographic research, and discourse/content analysis. Finally, it examines six issues that must be taken into account to ensure ethical research: voluntary participation, informed consent, privacy, harm, exploitation, and consequences for future research.