A quasi-experimental design is a type of research design that aims to establish a cause-and-effect relationship between an independent and dependent variable, similar to a true experiment. However, unlike a true experiment, quasi-experimental designs do not use random assignment of participants to conditions or orders of conditions. Instead, participants are assigned to groups based on pre-existing characteristics, such as age, gender, or eligibility criteria. Quasi-experimental designs are often used when randomization is impractical or unethical, making them easier to set up than true experimental designs.

Quasi-experimental designs have outcome measures, treatments, and experimental units, but do not use random assignment. There are several types of quasi-experimental designs, each with different strengths, weaknesses, and applications. Some of the most common types of quasi-experimental designs include:

• Difference in differences: This design compares the change in an outcome variable over time between a treatment group and a control group.
• Regression discontinuity: This design compares the outcomes of participants who are just above or below a threshold for receiving a treatment.
• Non-equivalent groups: This design compares the outcomes of participants in a treatment group to those in a non-treatment group that is similar in all other respects.
• Pretest-posttest: This design compares the outcomes of participants before and after a treatment.
• Natural experiments: This design takes advantage of naturally occurring events or circumstances that create a treatment and control group.

Quasi-experimental designs have lower internal validity than true experimental designs, but they often have higher external validity as they can use real-world settings and data. They are often conducted to evaluate the effectiveness of a treatment or intervention, such as a type of psychotherapy or an educational program[[5]](https://opentextbc.ca/researchmethods/chapter/quasi-experimental-res...