Nonexperimental Designs

Definition

Nonexperimental designs are research methods that lack the hallmark features of experiments, namely manipulation of independent variables and random assignment to conditions. The gold standard for scientific evidence in social psychology is the randomized experiment; however, there are many situations in social psychology in which randomized experiments are not possible or would not be the preferred method for data collection. Many social psychological variables cannot be manipulated, or ethics would keep one from doing so. For example, a researcher cannot randomly assign people to be in a relationship or not or to stay in a relationship for a long versus short period of time. Similarly, research participants cannot be randomly assigned to be male or female, homosexual or heterosexual, or Black or White. Therefore, the impact of important variables such as relationship status, culture, and ethnicity must be studied using nonexperimental designs.

Characteristics of Nonexperimental Research

Many nonexperimental studies address the same types of research questions addressed in experiments. They are aimed at testing whether the variable of interest causes people to react in certain ways to social stimuli. When this is the goal, nonexperimental studies often measure the variable of interest, often by asking people to report their beliefs or perceptions (such as measures of amount of self-confidence, of commitment to one's relationship, or of identification with one's ethnic group). Statistical analyses are then used to relate people's ratings to measures of other variables thought to be influenced by the initial variable. Consider a simple example in which a researcher wants to learn whether being committed to remaining in a romantic relationship leads people to be happier than not being committed to a relationship. This researcher might survey research participants who are in relationships, asking them to report their current level of commitment to the relationship and their current level of general happiness. A typical type of statistical analysis in this case might be to correlate relationship commitment with level of happiness. Because correlation is a common type of analysis in these designs, many people use the term correlational designs when they are actually referring to nonexperimental designs. The term nonexperimental is preferred primarily because the same correlational analyses could be performed on either nonexperimental or experimental data. The status of the study is determined by the research methods, not by the type of statistics used to analyze the data. Yet, the reader should understand that the terms correlational and nonexperimental are often used interchangeably.

If, in the previous example, the data show that people currently committed to their relationships are happier than are people not committed to their relationships, does this mean that being committed to a relationship makes people happier? Maybe, but maybe not. One of the major problems with nonexperimental designs is the result might have occurred in many [Page 624]ways. In this example, it could be that commitment to their current relationships does make people generally happier. However, it could be that people who are generally happier also make more attractive mates. People may flock to those who seem happy (and may want to stay with them), but may shy away from people who seem sullen and unhappy (and may want to leave them). If commitment loves company, being happy may also make people more likely to be committed to a relationship, rather than relationship commitment making people happier. It could also be that a third variable might encourage people to be committed to relationships and might also make people happy. For example, if the research participants are students, it could be that people who are doing well in school are happier than people not doing well in school. It could also be that people who are doing well in school have the time for social activities that draw them closer to their relationship partners. However, if people are doing poorly in school, spending more time outside of class studying to catch up (or the stress of struggling to catch up) may pull them farther away from their relationship partners. Third variables could also be called confounding variables, because they confound the original causal link that is hypothesized to exist between the two variables of interest.

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