Quasi-Experimental Designs
Real-World Causation • Partial Control • Applied Psychology
1. Introduction: Why Quasi-Experimental Designs?
In an ideal scientific setting, psychologists prefer true experimental designs with random assignment and full control. However, in many real-world situations, randomisation is impossible, unethical, or impractical.
Quasi-experimental designs emerge as a practical compromise—they aim to study cause–effect relationships while working within real social, educational, clinical, or organisational settings.
Quasi-experiments resemble true experiments, but lack random assignment of participants.
graph TD RP[Real-World Problem] --> QED[Quasi-Experimental Design] QED --> INT[Intervention] INT --> OUT[Outcome Comparison]
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2. Core Characteristics of Quasi-Experimental Designs
Quasi-experimental designs occupy the middle ground between experimental and non-experimental research.
Key Characteristics
- Manipulation of independent variable
- No random assignment to groups
- Use of pre-existing or naturally formed groups
- Partial control over extraneous variables
- High ecological validity
Comparing academic performance between two existing classrooms after introducing a new teaching method in one class.
graph TD IV[Independent Variable] --> DV[Dependent Variable] G1[Existing Group A] --> DV G2[Existing Group B] --> DV NOTE[No Random Assignment] -.-> G1 NOTE -.-> G2
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3. Major Types of Quasi-Experimental Designs
(a) Nonequivalent Control Group Design
Two or more existing groups are compared— one receives the treatment, the other does not.
graph LR G1[Group A] --> PRE1[Pre-test] PRE1 --> T[Treatment] T --> POST1[Post-test] G2[Group B] --> PRE2[Pre-test] PRE2 --> POST2[Post-test]
(b) Interrupted Time-Series Design
Repeated measurements are taken before and after an intervention to observe change over time.
graph LR T1[Observation 1] --> T2[Observation 2] T2 --> T3[Observation 3] T3 --> INT[Intervention] INT --> T4[Observation 4] T4 --> T5[Observation 5]
(c) Regression Discontinuity Design
Participants are assigned to groups based on a cutoff score rather than randomisation.
graph TD SCORE[Test Score] --> CUT[Cutoff Point] CUT --> TREAT[Treatment Group] CUT --> CTRL[Control Group]
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4. Advantages of Quasi-Experimental Designs
- Applicable in real-world settings
- Ethically acceptable when randomisation is not possible
- Higher external and ecological validity
- Useful for policy and program evaluation
Quasi-experiments bridge the gap between scientific control and social reality.
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5. Limitations of Quasi-Experimental Designs
- Lower internal validity than true experiments
- Selection bias due to non-random groups
- Confounding variables harder to control
- Causal conclusions must be cautious
Observed effects may be due to pre-existing group differences rather than intervention alone.
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6. Experimental vs Quasi-Experimental Designs (Quick Comparison)
| Aspect | Experimental | Quasi-Experimental |
|---|---|---|
| Random Assignment | Present | Absent |
| Control | High | Moderate |
| Internal Validity | High | Moderate |
| Ecological Validity | Lower | Higher |
| Field Applicability | Limited | High |
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