Quasi-Experimental Design: Definition, Types, and Examples

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Quasi-Experimental Design: Definition, Types, and Examples

Table of Contents
1. Definition of Quasi-Experimental Design
2. Quasi-Experimental vs. Experimental Design
3. Types of Quasi-Experimental Design
4. Applications in Educational Research
5. Examples of Research Paper By Discipline
6. Advantages and Disadvantages
7. Conclusion

Quasi-experimental design can be a valid option for determining the causal effects of interventions on outcomes when random assignment is not possible, not practical, or unethical. Quasi-experimental designs allow researchers to make causal inferences while attempting to approximate the conditions of a true experiment and operating within the limitations of real-world contexts.

Quasi-experimental designs are useful approaches for intervention research without random assignment, and they can be effectively one approach for applied research designs in education, healthcare, and social sciences. [1]

1. Definition of Quasi-Experimental Design

Quasi-experimental design is a quantitative research design that examines the impact of an intervention on a group, generally known as a target population, without random assignment of groups (treatment and control).  Quasi-experimental design is action-focused and shares many similar characteristics of experimental design – pretest, post-tests, control groups, etc. – but lacks random assignment (Schmidt & Brown, 2015), which is the fundamental difference. [1]

2. Quasi-Experimental vs. Experimental Design

Experimental vs Quasi-Experimental
Criteria Experimental Design Quasi-Experimental Design
Random Assignment Yes No
Internal Validity High Moderate to Low (depends on controls)
Control over Variables Strong Limited
Ethical Suitability Less suitable for real-world interventions More suitable for field or educational interventions
Example RCT of new drug Evaluating curriculum reform in public schools

3. Types of Quasi-Experimental Design

Quasi-Experimental Design Types
Type Description Example in Research Advantages Limitations
Non-Equivalent Control Group Design Compares a treatment group with a non-randomized control group Telerehabilitation Intervention in Transitional Care for People with COVID-19: Pre-Post Study with a Non-Equivalent Control Group [2] Allows group comparison Groups may differ in ways unrelated to intervention
Interrupted Time Series Design Observes data over time before and after intervention Improving Causal Inference in Observational Studies: Interrupted Time Series Design [3] Good for longitudinal analysis May be affected by other time-related factors
Regression Discontinuity Design Assigns participants to treatment/control based on a cutoff score Science of Science: A survey [4] Strong causal inference Requires large sample and precise cutoff
Single-Group Pretest–Post-test Design Measures outcomes before and after treatment in the same group Moving Beyond Simplistic Research Design in Health Professions Education: What a One-Group Pretest–Post-test Design Will Not Prove [5] Easy to implement No control group for comparison
Post-test-Only Design with Non-equivalent Groups Only measures outcomes after intervention in two or more non-randomized groups Can student–peers teach using simulated-based learning as well as faculty: A non-equivalent post-test-only study [6] Simple data collection No baseline data for comparison

4. Applications in Educational Research

Quasi experimental research design in education is needed when random assignment of either students or institutions is not possible. For example, policy interventions at the district or national level (such as digital education programs) usually use non-equivalent group designs to measure impact.

Example Scenarios:

  • Evaluating the impact of a remedial program in low-performing schools.
  • Investigating the exam post outcome of students studying using textbooks vs. e-learning.
  • Evaluating teacher training programs utilizing pretest-post-test designs.

5. Tools for Designing Graphical Abstracts

Quasi-Experimental Designs by Discipline
Discipline Example Design Used
Cardiology Designing and evaluating ECG interpretation software for undergraduate nursing students in Iran: a non-equivalent control group pretest-post-test design [7] Non-Equivalent Control Group Design
Psychology Mental Health Delivery Method Outcomes for the Postsecondary Student: A Quantitative Quasi-Experimental, Non-Equivalent Control Group Pretest-Post-test Study [8] Non-Equivalent Control Group Pretest-Post-test Study
Paediatric Development and evaluation of a paediatric nursing competency-building program for nursing students in South Korea: a quasi-experimental study [9] Quasi-experimental study, non-equivalent control group pretest-post-test design
Nursing Effect of the Management in Nursing course on students’ time management and career planning attitudes: A single-group pre-test post-test study [10] A single-group pre-test post-test study
Cardiology Integrating mixed reality preparation into acute coronary syndrome simulation for nursing students: a single-group pretest-posttest study [11] A single-group pre-test post-test study
General Teacher training and HIV/AIDS prevention in West Africa: regression discontinuity design evidence from the Cameroon [12] Regression discontinuity design
Health Care Use of Interrupted Time Series Analysis in Evaluating Health Care Quality Improvements [13] Interrupted Time Series Design
Health Service Emergency department-based medication review on outpatient health services utilization: interrupted time series [14] Interrupted Time Series Design
Medical Intensive Care Mortality, Morbidity, and Costs After Implementation of a Vasopressin Guideline in Medical Intensive Care Patients With Septic Shock: An Interrupted Time Series Analysis [15] Interrupted Time Series Design

6. Advantages and Disadvantages

Advantages and Disadvantages of Quasi-Experimental Designs
Advantages of Quasi-Experimental Designs Disadvantages of Quasi-Experimental Designs
  • Problem-based research designs are well-suited to applied research in real-world contexts.
  • A problem-based design allows for intervention studies without the need for random assignment.
  • Problem-based research designs are generally more ethical and manageable than randomized control trials.
  • A problem-based research design supports policy evaluations and large-scale educational reforms.
  • More likely to be affected by selection bias.
  • May not have as much internal validity as randomized experiments.
  • Requires careful statistical control of confounding variables.
  • Causality is harder to establish in absence of randomization.

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Conclusion

Quasi-experimental designs effectively address research settings without control or randomization; in fact, they have aspects of both observational research with an intervention and controlled experiments. Quasi-experimental designs are commonplace in the fields of education, public health, and policy analysis which mix elements of both observational research and experimentation. If researchers understand the types, uses, and limitations of quasi-experimental designs, it can help them to develop studies that achieve an appropriate level of feasibility without sacrificing scientific rigor.

Quasi-Experimental Design: Definition, Types, and Examples? Pubrica offers end-to-end research design, analysis, and reporting support.

References

  1. Quasi-Experimental Design: Definition, types, examples. (2023, December 19). com. https://www.appinio.com/en/blog/market-research/quasi-experimental-design
  2. Reis, N., Costa Dias, M. J., Sousa, L., Canedo, F., Rico, M. T., Henriques, M. A., & Baixinho, C. L. (2023). Telerehabilitation Intervention in Transitional Care for People with COVID-19: Pre-Post Study with a Non-Equivalent Control Group. Healthcare, 11(18), 2561. https://doi.org/10.3390/healthcare11182561
  3. Kim, K.-N. (2020). Improving causal inference in observational studies: Interrupted time series design. Cardiovascular Prevention and Pharmacotherapy, 2(1), 18. https://doi.org/10.36011/cpp.2020.2.e2
  4. Li, M., Zhang, Y., & Wang, Y. (2023). Regression discontinuity design and its applications to Science of Science: A survey. Journal of Data and Information Science, 8(2), 43–65. https://doi.org/10.2478/jdis-2023-0008
  5. Bierer, S. B., Beck Dallaghan, G., Borges, N. J., Brondfield, S., Fung, C. C., Huggett, K. N., Teal, C. R., Thammasitboon, S., & Colbert, C. Y. (2025). Moving Beyond Simplistic Research Design in Health Professions Education: What a One-Group Pretest-Posttest Design Will Not Prove. MedEdPORTAL : the journal of teaching and learning resources, 21, 11527. https://doi.org/10.15766/mep_2374-8265.11527
  6. Dennis, D., Furness, A., Brosky, J., Owens, J., & Mackintosh, S. (2020). Can student-peers teach using simulated-based learning as well as faculty: A non-equivalent posttest-only study. Nurse Education Today, 91(104470), 104470. https://doi.org/10.1016/j.nedt.2020.104470
  7. Kohan, N., Navabi, N., Motlagh, M. K., & Ahmadinia, F. (2024). Designing and evaluating ECG interpretation software for undergraduate nursing students in Iran: a non-equivalent control group pretest-posttest design. BMC Nursing, 23(1), 827. https://doi.org/10.1186/s12912-024-02472-0
  8. Jun, S., & Lee, H. (2024). Information-Motivation-Behavioral Skill model-based physical restraint education program for nursing care providers in long-term care hospitals: A quasi-experimental repeated measures non-equivalent control group design. Journal of Korean Gerontological Nursing, 26(3), 288–301. https://doi.org/10.17079/jkgn.2024.00402
  9. Koo, H. Y., & Lee, B. R. (2022). Development and evaluation of a pediatric nursing competency-building program for nursing students in South Korea: a quasi-experimental study. Child Health Nursing Research, 28(3), 167–175. https://doi.org/10.4094/chnr.2022.28.3.167
  10. Çingöl, N., & Karakaş, M. (2023). Effect of the Management in Nursing course on students’ time management and career planning attitudes: A single-group pre-test post-test study. Nurse Education Today, 125(105797), 105797. https://doi.org/10.1016/j.nedt.2023.105797
  11. Moon, S.-H., Jeong, H., & Choi, M. J. (2024). Integrating mixed reality preparation into acute coronary syndrome simulation for nursing students: a single-group pretest-posttest study. BMC Nursing, 23(1),468. https://doi.org/10.1186/s12912-024-02110-9
  12. Arcand, J.-L., & Wouabe, E. D. (2010). Teacher training and HIV/AIDS prevention in West Africa: regression discontinuity design evidence from the Cameroon. Health Economics, 19 Suppl(S1), 36–54. https://doi.org/10.1002/hec.1643
  13. Penfold, R. B., & Zhang, F. (2013). Use of interrupted time series analysis in evaluating health care quality improvements. Academic Pediatrics, 13(6 Suppl), S38-44. https://doi.org/10.1016/j.acap.2013.08.002
  14. Kitchen, S. A., McGrail, K., Wickham, M. E., Law, M. R., & Hohl, C. M. (2020). Emergency department-based medication review on outpatient health services utilization: interrupted time series. BMC Health Services Research, 20(1), 254. https://doi.org/10.1186/s12913-020-05108-6
  15. Bauer, S. R., Sacha, G. L., & Reddy, A. J. (2020). Mortality, morbidity, and costs after implementation of a vasopressin guideline in medical intensive care patients with septic shock: An interrupted time series analysis. The Annals of Pharmacotherapy, 54(4), 314–321. https://doi.org/10.1177/1060028019886306

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