12.2: Introduction to Nonexperimental Research

Learning Objectives

1. Define non-experimental research, distinguish it clearly from experimental research.
2. Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

Non-experimental research is research that lacks the manipulation of an independent variable and does not require initial equivalence between the comparison groups. Because of this, the studies lack internal validity and cannot be used to determine cause and effect relationships. However, recall the three goals of science discussed in section 2.2 (Goals of Science).

Exercise \(\PageIndex{1}\)

Describe each of the three goals of science discussed in chapter 2.

Answer

The three goals of science are:

• Desciption: This goal is to describe reality and individuals' experiences.
• Prediction: This goal is to use one variable to predict the outcome of another variable.
• Intervention: This goal is to improve behavior and experiences based on causal relationships between variables.

Do all of these goals need to determine cause-and-effect relationships? No! The goal of description definitely does not need to determine the cause of why things are as they are. And with our knowledge of "correlation is no causation" or "What about Z?", we know that just because variables are related (and can be used to predict each other) doesn't mean that one variable caused changes in the other.

While most social science researchers consider the distinction between experimental and non-experimental research to be an extremely important one because experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research. It is simply used when the goal is not (yet?) intervention.

When to Use Non-Experimental Research

As we have seen throughout this textbook, experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when:

• The research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., how accurate are people’s first impressions?).
• The research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
• The research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
• The research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. But the two approaches can also be used to address the same research question in complementary ways. For example, in Milgram’s original (non-experimental) obedience study, he was primarily interested in one variable—the extent to which participants obeyed the researcher when he told them to shock the confederate—and he observed all participants performing the same task under the same conditions. However, Milgram subsequently conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974).

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure \(\PageIndex{1}\) shows how experimental, quasi-experimental, and non-experimental research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) with initial equivalence and ongoing equivalence between the IV groups help to rule out alternative explanations for any changes found in the DV. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental research is lowest in internal validity because these designs fail to use manipulation or control; but this doesn't mean that non-experimental studies are bad! Researchers have different topics and different goals, and sometimes non-experimental designs are the most appropriate. Quasi-experimental research falls in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the inability to randomly assign children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Figure \(\PageIndex{1}\): Internal Validity of Correlation, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlation (non-experimental) studies lower still.

Notice also in Figure \(\PageIndex{1}\) that there is some overlap in the internal validity of experiments, quasi-experiments, and non-experimental studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

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References

Milgram, S. (1974). Obedience to authority: An experimental view. New York, NY: Harper & Row.