Question

How does the concept of “equivalent groups” relate to the experiment and the quasi-experiment?

Answer 1

A quasi-experimental research design is the use of methods and procedures to make observations in a study that is structured similar to an experiment, but the conditions and experiences of participants lack some control because the study lacks random assignment, includes a preexisting factor

Quasi-Experiment: Definitions

I'm going to do a psychological experiment where I make people different ages and then see how they react to loud noises. Well, I'd like to. Unfortunately, even with our advanced quantum physics and computers, we cannot reverse or control age like that. Psychological researchers are forced to work around the issue.

Because we can't reverse someone's age, we have to work with people who are already that age. But, we miss some things in the process. But, I'm getting ahead of myself.

A true experiment has one main component - randomly assigned groups. This translates to every participant having an equal chance of being in the experimental group, where they are subject to a manipulation, or the control group, where they are not manipulated.A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population without random assignment. ...Quasi-experiments are subject to concerns regarding internal validity, because the treatment and control groups may not be comparable at baseline.

Ethics[edit]

A true experiment would, for example, randomly assign children to a scholarship, in order to control for all other variables. Quasi-experiments are commonly used in social sciences, public health, education, and policy analysis, especially when it is not practical or reasonable to randomize study participants to the treatment condition.

As an example, suppose we divide households into two categories: Households in which the parents spank their children, and households in which the parents do not spank their children. We can run a linear regression to determine if there is a positive correlation between parents' spanking and their children's aggressive behavior. However, to simply randomize parents to spank or to not spank their children may not be practical or ethical, because some parents may believe it is morally wrong to spank their children and refuse to participate.

Some authors distinguish between a natural experiment and a "quasi-experiment".^[1][5] The difference is that in a quasi-experiment the criterion for assignment is selected by the researcher, while in a natural experiment the assignment occurs 'naturally,' without the researcher's intervention.

Quasi-experiments have outcome measures, treatments, and experimental units, but do not use random assignment. Quasi-experiments are often the design that most people choose over true experiments. The main reason is that they can usually be conducted while true experiments can not always be. Quasi-experiments are interesting because they bring in features from both experimental and non experimental designs. Measured variables can be brought in, as well as manipulated variables. Usually Quasi-experiments are chosen by experimenters because they maximize internal and external validity

A quasi-experiment is simply defined as not a true experiment. Since the main component of a true experiment is randomly assigned groups, this means a quasi-experiment does not have randomly assigned groups. Why are randomly assigned groups so important since they are the only difference between quasi-experimental and true experimental?

When performing an experiment, a researcher is attempting to demonstrate that variable A influences or causes variable B to do something. They want to demonstrate cause and effect. Random assignment helps ensure that there is no pre-existing condition that will influence the variables and mess up the results.

A silly example would be something like, 'Does chemical X1 cause blindness?' If you accidentally put all of the people wearing glasses in the condition where you spray X1 in someone's face, then your results are going to be skewed. This is an extreme and overly simplistic example, but it is demonstrating why normally an experimenter wants to randomly assign people into different groups. Let's look at some more realistic and typical quasi-experiments in psychology.

Advantages[edit]

Since quasi-experimental designs are used when randomization is impractical and/or unethical, they are typically easier to set up than true experimental designs, which require^[9]random assignment of subjects. Additionally, utilizing quasi-experimental designs minimizes threats to ecological validity as natural environments do not suffer the same problems of artificiality as compared to a well-controlled laboratory setting.^[10] Since quasi-experiments are natural experiments, findings in one may be applied to other subjects and settings, allowing for some generalizations to be made about population. Also, this experimentation method is efficient in longitudinal research that involves longer time periods which can be followed up in different environments.

Other advantages of quasi experiments include the idea of having any manipulations the experimenter so chooses. In natural experiments, the researchers have to let manipulations occur on their own and have no control over them whatsoever. Also, using self selected groups in quasi experiments also takes away to chance of ethical, conditional, etc. concerns while conducting the study.^[8]

Disadvantages[edit]

Quasi-experimental estimates of impact are subject to contamination by confounding variables.^[1] In the example above, a variation in the children's response to spanking is plausibly influenced by factors that cannot be easily measured and controlled, for example the child's intrinsic wildness or the parent's irritability. The lack of random assignment in the quasi-experimental design method may allow studies to be more feasible, but this also poses many challenges for the investigator in terms of internal validity. This deficiency in randomization makes it harder to rule out confounding variables and introduces new threats to internal validity.^[11] Because randomization is absent, some knowledge about the data can be approximated, but conclusions of causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. Moreover, even if these threats to internal validity are assessed, causation still cannot be fully established because the experimenter does not have total control over extraneous variables.^[12]

Disadvantages also include the study groups may provide weaker evidence because of the lack of randomness. Randomness brings a lot of useful information to a study because it broadens results and therefore gives a better representation of the population as a whole. Using unequal groups can also be a threat to internal validity. If groups are not equal, which is sometimes the case in quasi experiments, then the experimenter might not be positive what the causes are for the results.^[4]

Internal validity[edit]

Internal validity is the approximate truth about inferences regarding cause-effect or causal relationships. This is why validity is important for quasi experiments because they are all about causal relationships. It occurs when the experimenter tries to control all variables that could affect the results of the experiment. Statistical regression, history and the participants are all possible threats to internal validity. The question you would want to ask while trying to keep internal validity high is "Are there any other possible reasons for the outcome besides the reason I want it to be?" If so, then internal validity might not be as strong.^[8]

External validity[edit]

External validity is the extent to which results obtained from a study sample can be generalized to the population of interest. When External Validity is high, the generalization is accurate and can represent the outside world from the experiment. External Validity is very important when it comes to statistical research because you want to make sure that you have a correct depiction of the population. When external validity is low, the credibility of your research comes into doubt. Reducing threats to external validity can be done by making sure there is a random sampling of participants and random assignment as well.^[13]

Design types[edit]

"Person-by-treatment" designs are the most common type of quasi experiment design. In this design, the experimenter measures at least one independent variable. Along with measuring one variable, the experimenter will also manipulate a different independent variable. Because there is manipulating and measuring of different independent variables, the research is mostly done in laboratories. An important factor in dealing with person-by-treatment designs are that random assignment will need to be used in order to make sure that the experimenter has complete control over the manipulations that are being done to the study.^[14]

An example of this type of design was performed at the University of Notre Dame. The study was conducted to see if being mentored for your job led to increased job satisfaction. The results showed that many people who did have a mentor showed very high job satisfaction. However, the study also showed that those who did not receive the mentor also had a high number of satisfied employees. Seibert concluded that although the workers who had mentors were happy, he could not assume that the reason for it was the mentors themselves because of the numbers of the high number of non-mentored employees that said they were satisfied. This is why prescreening is very important so that you can minimize any flaws in the study before they are seen.^[15]

"Natural experiments" are a different type of quasi experiment design used by researchers. It differs from person-by-treatment in a way that there is not a variable that is being manipulated by the experimenter. Instead of controlling at least one variable like the person-by-treatment design, experimenters do not use random assignment and leave the experimental control up to chance. This is where the name "natural" experiment comes from. The manipulations occur naturally, and although this may seem like an inaccurate technique, it has actually proven to be useful in many cases. These are the studies done to people who had something sudden happen to them. This could mean good or bad, traumatic or euphoric. An example of this could be studies done on those who have been in a car accident and those who have not. Car accidents occur naturally, so it would not be ethical to stage experiments to traumatize subjects in the study. These naturally occurring events have proven to be useful for studying posttraumatic stress disorder cases