What is Quasi-Experimental Design? Definition, Types, and Examples

An experimental design is the process of planning and organizing scientific experiments to obtain useful results from collected data. Experimental design is an important aspect of the scientific method because it ensures the validity and reliability of the information extracted from available data. In several experimental designs, objects or participants are randomly assigned to an experimental group to avoid any type of bias; these are called true experiments. 

A quasi-experimental design is a study design in which participants cannot be randomly assigned to an experimental or control group for practical or ethical reasons. However, like a true experiment, it is used to evaluate the effects of an intervention, or in other words, to establish a cause-and effect relationship between independent and dependent variables. The intervention could be a training program, a policy change, a medical treatment, etc. In such quasi-experimental designs, the assignment of participants is usually based on self-selection or selection by an administrator or researcher.  

This article will provide the quasi-experimental design definition and will describe in detail the types and uses of such experimental designs and their similarities and differences with true experiments. 

What is Quasi-Experimental Research? 

The prefix “quasi” means “resembling to a certain degree.” Accordingly, the definition of quasi-experimental research1,2 is that it is a type of research that resembles true experimental research but is not the exact same concept. A true experimental design has three characteristics—manipulation of the independent variable, presence of a control group, and random assignment of participants to experimental groups. 

In quasi-experimental research, although the independent variable is manipulated, either the participants are not randomly assigned to groups or there is no control group. This is the main difference between quasi and true experiments. 

In quasi-experimental research, the directionality problem (that is, the relationship between two variables is known but the cause and effect is not known) doesn’t exist because of the ability to manipulate independent variables. However, this type of research doesn’t eliminate the problem of confounding variables (an extraneous variable that is not controlled in a study and could affect other variables, resulting in distorted associations between the variables) because quasi-experimental research doesn’t involve random assignment. Consequently, quasi-experimental research is lower in internal validity (the extent to which a study can establish a cause-and-effect relationship between variables) than true experiments. 

Quasi-experimental research is most common in field studies where random assignment is either difficult or impossible. This type of research is often conducted to analyze the effectiveness of a specific treatment. Some of the important types of quasi-experimental research designs are—non-equivalent group design, pretest–posttest design, interrupted time series design, combination design, and regression discontinuity design. After understanding the quasi experimental design meaning, let’s look at when to use this. 

When to Use Quasi-Experimental Research?  

In some situations, using randomization to assign participants to groups may be unethical (for example, providing a specific health treatment to one group and withholding it from the other group). In such cases, quasi-experimental research can be used to identify a causal relationship without any ethical or practical challenges.  

The following list describes some instances, with examples, where quasi-experimental research designs would be more appropriate.3,4 

1. When being in one group could be harmful to the participants either because the intervention is harmful (e.g., randomizing people to smoking), or the intervention has questionable efficacy, or it is so beneficial that it wouldn’t be appropriate to withhold the intervention from the control group (e.g., randomizing people to receive a minor surgery). 
2. When interventions act on a group of people in a specific location, it becomes difficult to adequately randomize participants (e.g., an intervention that reduces pollution in a specific area). 
3. When working with small sample sizes, because randomized controlled trials require a large sample size to ensure even distribution of confounding variables between the treatment and control groups. 

Differences Between Quasi Experiments and True Experiments  

Unsure about choosing between experimental and quasi-experimental design for your research? Take a look at the main differences between quasi and true experiments as depicted in the following table.4,5 

Types of Quasi-Experimental Designs  

Here are some common types of quasi-experimental designs.[1,5] 

Non-equivalent Groups Design 

In a between-subjects experimental design, participants are randomly divided into two or more groups and each group is assigned a treatment condition, the outcomes of which are then compared. In such designs, the resulting groups are quite similar and are considered equivalent. However, when participants are not randomly assigned, the groups will be dissimilar and are therefore considered non-equivalent. The groups may have preexisting differences that could affect the outcome of the study because it becomes difficult to attribute any observed changes solely to the intervention being studied. This type of research design is one of the most common quasi-experimental designs.  

Pretest–Posttest Design 

In this type of research design, the dependent variable is measured once before the treatment begins and once after the treatment. For example, a researcher interested in studying the effectiveness of a public-speaking short seminar on elementary school students’ speaking skills could analyze the skills of the children before the course and then after the course to identify any changes. This type of quasi-experimental design is similar to a within-subjects experiment in which each participant is tested first under the control condition and then under the treatment condition. If the average posttest score is better than the average pretest score, it implies that the treatment may be responsible for the improvement. This research design may or may not include control groups and may be prone to internal validity risk (this is the main difference of this design with the non-equivalent groups design). One advantage of this quasi-experimental design is that it provides directionality because the dependent variable is tested both before and after the intervention. 

Combination Design 

This type of quasi-experimental design combines both pretest–posttest and non-equivalent groups designs. In this research design, a treatment group is given a pretest, receives a treatment, and then is given a posttest. The control group is also given a pretest, but does not receive the treatment, and then is given a posttest. 

Interrupted Time Series Design 

A time series is a set of measurements taken at multiple and equally spaced intervals over a period of time before and after an intervention. The main objective of this type of quasi-experimental design is to assess whether the observations before and after the intervention are different. For example, a company wants to measure its employees’ productivity per week for a year. In this type of research design, a time series is “interrupted” by a treatment. In this same example, the company reduced work hours from 10 hours to 8 hours. This measure was found to increase the productivity quickly and it remained elevated for several months. This would help researchers conclude that reduced work hours increased productivity. 

Regression Discontinuity Design 

This quasi-experimental design assesses the influence of a treatment or intervention by using a mechanism that assigns the treatment based on eligibility, or a “cut-off point” of some known variable, such as age and income. This specific threshold value or cut-off score is used to assign participants to treatment groups and helps researchers compare the effectiveness of an intervention on participants immediately above and below the cut-off point. 

Advantages and Disadvantages of Quasi-Experimental Designs 

Here are a few important advantages and disadvantages of quasi-experimental designs.3,6 

Advantages of Quasi-Experimental Designs 

1. Higher external validity: Quasi-experimental designs are more practical with more real-world applications and therefore may be more generalizable. 
2. Higher control over targeted hypotheses: Because there is no randomization of participants, the dependent variables can be more controlled, targeted, and efficient. 
3. Can be combined with other methodologies: Quasi-experimental design can be combined with statistical analyses and results of other true experiments, which can significantly reduce research time. 
4. Less expensive and time consuming than randomized controlled trials and require fewer resources. 

Disadvantages of Quasi-Experimental Designs  

1. Randomization is not used, so the study is not useful for concluding a causal relationship between an intervention and an outcome. 
2. Lower internal validity: Because the variables can be controlled, it’s difficult to know if researchers have used all confounding variables. 
3. Risk of inaccurate data: Quasi-experimental design often borrows data from other research so the data may not necessarily be complete or accurate. 
4. Risk of bias: Researchers choose baseline elements and eligibility so there’s a risk of researcher bias. The types of selection bias that can occur in quasi-experimental design include maturation bias, historical bias, instrumentation bias, and Hawthorne effect. 

Key Takeaways 

• Both experimental and quasi-experimental designs are used to evaluate the effectiveness of a treatment. 

• Quasi experiments differ from true experiments in several aspects: 

• Participants cannot be randomly selected or assigned to treatment groups for practical or ethical reasons. 

• A control group may or may not be necessary 

• Quasi experiments have high external validity, are useful for smaller sample sizes, are less expensive, and they require fewer resources. 

• Quasi-experimental designs have low internal validity, and the absence of randomization leads to a risk of bias and confounding. 

• Some of the important types of quasi-experimental designs are—non-equivalent group design, pretest–posttest design, interrupted time series design, combination design, and regression discontinuity design. 

Frequently Asked Questions  

Q1. What is the main purpose of quasi-experimental research? 

A1. The main purpose of quasi-experimental research is to establish a cause-and-effect relationship between variables and assess the impact of an intervention on the outcome, in the absence of randomization. 

Q2. What are some applications of quasi-experimental design in research? 

A2. Quasi-experimental designs can be used in different disciplines, some of which are mentioned below.7 

• Education: Quasi-experimental design can be used in education to assess the effectiveness of diverse interventions, such as new teaching measures and tools, curriculum changes, teacher training, policy changes, etc. 

• Healthcare: To analyze the effectiveness of new medicines, dosages, medical equipment, etc. 

• Psychology: To study the influence of factors such as trauma, geographic changes, social media, etc., on behavior. 

• Public policy: To examine the influence of policy changes and government reforms on the public, such as the effect of new tax reforms on spending power. 

• Business and marketing: To analyze the effects of new products, advertisements through different media, product design, etc., on consumer behavior and the purchasing trends of consumers. 

Q3. What are a few real-world quasi-experimental research examples? 

A3. Here are a few quasi-experimental research examples in the real-world setting.7 

Education 

To study the effectiveness of a new or updated educational program or curriculum, you could use the non-equivalent groups design method to select two schools with comparable features within the same district, introduce the new program in one, and retain the existing programs in the other. Comparison between the schools after a specific period can help ascertain whether the new program was effective or not. Random assignment of the schools or student groups would not have been appropriate because it could have been rendered advantageous or disadvantageous to either group. 

Healthcare 

Quasi-experimental research can be helpful in analyzing the effectiveness of public health interventions such as vaccination campaigns. A time-series quasi-experimental design would be useful in understanding the effect of vaccination over a prolonged period by studying disease incidence rates before and after vaccination. 

Workplace 

A company can evaluate the effectiveness of a technical skills training program for its employees using the pretest-posttest quasi-experimental design. The technical skills of the employees can be tested both before and after they participate in the training. This research design focuses on immediate impact unlike the time series design, which focuses on the impact over a long period. 

A quasi-experimental design is thus very similar to true experiments, with the same objective of assessing the effectiveness of interventions in various fields. However, it has certain characteristically important differences, which render such designs useful in situations where conducting a true experiment may not be ethical or practical. We hope this article would have expanded your knowledge of experimental and quasi-experimental designs and will help you in selecting the appropriate design for your research. 

References 

1. Price PC, Jhangiani R, Chiang I-C A. Quasi-experimental research. Research Methods in Psychology – 2nd Canadian edition. BCCampus website. Accessed November 12, 2024. https://opentextbc.ca/researchmethods/chapter/quasi-experimental-research/ 
2. Price PC et al. Chapter 8: Quasi-experimental research. Research Methods in Psychology. Accessed November 13, 2024. https://opentext.wsu.edu/carriecuttler/part/chapter-8-quasi-experimental-research/ 
3. Quasi-experimental design: Types, examples, pros, and cons. MasterClass website. Published June 16, 2022. Accessed November 14, 2024. https://www.masterclass.com/articles/quasi-experimental 
4. Choueiry G. Experimental vs. quasi-experimental design: Which to choose? Quantifying Health. Accessed November 14, 2024. https://quantifyinghealth.com/experimental-vs-quasi-experimental-design/ 
5. Explaining quasi-experimental design and its various methods. Voxco. Published September 17, 2021. Accessed November 15, 2024. https://www.voxco.com/blog/quasi-experimental-design-explanation-methods-and-faqs/ 
6. Schweizer ML, Braun BI, Milstone AM. Research methods in healthcare epidemiology and antimicrobial stewardship-quasi experimental designs. Infect Control Hosp Epidemiol. 2016;37(10):1135-40. doi:10.1017/ice.2016.117. Accessed November 16, 2024. https://pmc.ncbi.nlm.nih.gov/articles/PMC5036994/ 
7. Quasi-experimental design: Rigor meets real-world conditions. Servicescape. Published October 4, 2023. Accessed November 18, 2024. https://www.servicescape.com/blog/quasi-experimental-design-rigor-meets-real-world-conditions 

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