This chapter focuses on different research designs in experimental sociology. Most definitions of what constitutes an experiment converge on the idea that the experimenter "control" the phenomenon under investigation, thereby setting the conditions under which the phenomenon is observed and analyzed. Typically, the researcher exerts experimental control by creating two situations that are virtually identical, except for one element that the researcher introduces or manipulates in only one of the situations. The purpose of this exercise is to observe the effects of such manipulation by comparing it with the outcomes of the situation in which the manipulation is absent. One way to look at how the implementation of this rather straightforward exercise produces a variety of designs is by focusing on the relationship that experimental design bears with the theory that inspires it. Therefore, we begin this chapter with a discussion of the relationship between theory and experimental design before turning to a description of the most important features of various types of designs. The chapter closes with a short overview of experiments in different settings such as laboratory, field, and multifactorial survey experiments.

Experimental practices developed in different scientific disciplines following different historical trajectories. Thus, standard experimental procedures differ starkly between disciplines. One of the most controversial issues is the use of deception as a methodological device. Psychologists do not conduct a study involving deception unless they have determined that the use of deceptive techniques is justified by the study’s significant prospective scientific, educational, or applied value and that effective nondeceptive alternative procedures are not feasible. In experimental economics it is strictly forbidden and a ban on experiments involving deception is enforced by all major economic journals. In the sociological scientific community, there is no clear consensus on the matter. Importantly, the disagreement is sometimes based on ethical considerations, but more often it is based on pragmatic grounds: the anti-deception camp argues that deceiving participants leads to invalid results, while the other side argues that deception has little negative impact and, under certain conditions, can even enhance validity. In this chapter, we first discuss the historical reasons leading to the emergence of such different norms in different fields and then analyze and separate ethical and pragmatic concerns. Finally, we propose some guidelines to regulate the use of deception in sociological experiments.

Sociology is a science concerning itself with the interpretive understanding of social action and thereby with a causal explanation of its course and consequences. Empirically, a key goal is to find relations between variables. This is often done using naturally occurring data, survey data, or in-depth interviews. With such data, the challenge is to establish whether a relation between variables is causal or merely a correlation. One approach is to address the causality issue by applying proper statistical or econometric techniques, which is possible under certain conditions for some research questions. Alternatively, one can generate new data with experimental control in a laboratory or the field. It is precisely through this control via randomization and the manipulation of the causal factors of interest that the experimental method ensures – with a high degree of confidence – tests of causal explanations. In this chapter, the canonical approach to causality in randomized experiments (the Neyman–Rubin causal model) is first introduced. This model formalizes the idea of causality using the "potential outcomes" or "counterfactual" approach. The chapter then discusses the limits of the counterfactual approach and the key role of theory in establishing causal explanations in experimental sociology.

Field experiments have a long tradition in some areas of the social and behavioral sciences and have become increasingly popular in sociology. Field experiments are staged in "natural" research settings where individuals usually interact in everyday life and regularly complete the task under investigation. The implementation in the field is the core feature distinguishing the approach from laboratory experiments. It is also one of the major reasons why researchers use field experiments; they allow incorporating social context, investigating subjects under "natural" conditions, and collecting unobtrusive measures of behavior. However, these advantages of field experiments come at the price of reduced control. In contrast to the controlled setting of the laboratory, many factors can influence the outcome but are not under the experimenter’s control and are often hard to measure in the field. Using field experiments on the broken windows theory, the strengths and potential pitfalls of experimenting in the field are illustrated. The chapter also covers the nascent area of digital field experiments, which share key features with other types of experiments but offer exciting new ways to study social behavior by enabling the collection large-scale data with fine-grained and unobtrusive behavioral measures at relatively low variable costs.

This chapter focuses in more detail on the role of incentives in experimental sociology. Providing the right incentives in an experiment is an important precondition for drawing valid inferences. This is a predominant view in experimental economics based on the induced-value theory assuming that monetary incentives override any other human motivation in laboratory economic experiments. A slightly less demanding assumption is that subjects can be incentivized by monetary payoffs but are also motivated by other-regarding preferences or reciprocity. On the other hand, psychologists focus on motivations that subjects bring into the laboratory as a predisposition to behavior and on the framing of the situation. Sociological research takes elements from both perspectives and emphasizes institutional, cultural, and social determinants of human behavior. An important theoretical framework for experimental work is sociological work on framing. According to sociological framing theories, subjects interpret the situation in terms of the given cues and select an action that is appropriate to the situation. The chapter discusses the implications of these three views on the design of experiments in sociology.

The discipline of sociology focuses on interactions and group processes from the perspective of emergent phenomena at the social level. Concepts like social embedding, norms, group-level motivation, or status hierarchies can only be defined and conceptualized in contexts in which individuals are involved in social interaction. Such concepts share the property of being social facts that cannot be changed by individual intention alone and that require some element of individual adjustment to the socially given condition. Sociologists study the embeddedness of individual motivations or preferences in the context of social phenomena as such and the impact of these phenomena on individual adaptation. However, these phenomena can only be observed in individual human behavior, and this tension between the substantive focus on the aggregate level and the analytical focus on the individual level is the challenge that sociological experiments confront.

In the introduction, the field of experimental sociology is outlined and the core concepts of manipulation and control, as well as two crucial conditions of control, are introduced. The random allocation of participants to the treatment and the control group ensures that exogenous factors are distributed equally across these groups, which allows to evaluate the effect of the manipulated condition. Incentivization helps operationalizing behavioral assumptions into the experimental condition. The chapter then briefly elaborates on the topics of the following chapters.

This chapter summarizes the main points of the book and reflects on possible ways ahead for experimental sociology.

Laboratory experiments are the type of study that most people have in mind when talking about experiments. In this chapter, we first discuss the strengths of laboratory experiments, which offer the highest degree of experimental control as compared to other types of experiments. Single factors can be manipulated according to the requirements of theories under highly controlled conditions. As such, laboratory experiments are well-placed to test theories. We then introduce a sociological laboratory experiment as a leading example, which we use as a reference for a discussion of several principles of laboratory research. Furthermore, we discuss a second goal of laboratory experiments, which is the establishment of empirical regularities in situations where theory does not provide sufficient guidance for deriving behavioral expectations. The chapter concludes with a short discussion of caveats for the analysis of sociological data generated in laboratory experiments.

Vignette experiments are vignettes are brief descriptions of social objects including a list of varying characteristics, on the basis of which survey respondents state their evaluations or judgments. The respondents’ evaluations typically concern positive beliefs, normative judgments, or their own intentions or actions. Using a study on the gender pay gap and an analysis of trust problems in the purchase of used cars as examples, we discuss the design characteristics of vignettes. Core issues are the selection of the vignettes that are included out of the universe of possible combinations, the type of dependent variables, such as rating scales or ranking tasks, the presentation style, differentiating text vignettes from a tabular format, and issues related to sampling strategies.

This chapter addresses the often-misunderstood concept of validity. Much of the methodological discussion around sociological experiments is framed in terms of internal and external validity. The standard view is that the more we ensure that the experimental treatment is isolated from potential confounds (internal validity), the more unlikely it is that the experimental results can be representative of phenomena of the outside world (external validity). However, other accounts describe internal validity as a prerequisite of external validity: Unless we ensure internal validity of an experiment, little can be said of the outside world. We contend in this chapter that problems of either external or internal validity do not necessarily depend on the artificiality of experimental settings or on the laboratory–field distinction between experimental designs. We discuss the internal–external distinction and propose instead a list of potential threats to the validity of experiments that includes "usual suspects" like selection, history, attrition, and experimenter demand effects and elaborate on how these threats can be productively handled in experimental work. Moreover, in light of the different types of experiments, we also discuss the strengths and weaknesses of each regarding threats to internal and external validity.