Model Answer
0 min readIntroduction
Factorial designs are crucial in psychological research, allowing investigation of multiple independent variables and their interactions. These designs can be broadly categorized into ‘within-subjects’ (repeated measures) and ‘between-subjects’ designs. Understanding the distinction between these approaches is fundamental to designing robust and interpretable experiments. Both designs aim to examine the effects of two or more independent variables on a dependent variable, but they differ significantly in how participants are assigned to conditions and how data is analyzed.
Within-Factorial Design
In a within-factorial design, the same participants are exposed to all levels of each independent variable. This means each participant serves as their own control. This design reduces the impact of individual differences on error variance, increasing statistical power.
Between-Factorial Design
Conversely, a between-factorial design assigns different participants to each level of the independent variable. Each participant experiences only one condition. This design avoids carryover effects (order effects) but is susceptible to larger error variance due to individual differences between groups.
Key Differences: A Comparison
| Feature | Within-Factorial Design | Between-Factorial Design |
|---|---|---|
| Participant Allocation | Same participants in all conditions | Different participants in each condition |
| Error Variance | Lower (individual differences controlled) | Higher (individual differences contribute) |
| Statistical Power | Higher | Lower |
| Carryover Effects | Potential issue (requires counterbalancing) | Not an issue |
The choice between these designs depends on the research question and potential confounding variables. Within-subjects designs are suitable when carryover effects can be minimized, while between-subjects designs are preferred when carryover effects are likely or when individual differences are a primary interest.
Conclusion
In essence, within-factorial designs leverage individual participant data to enhance statistical power and control for individual differences, while between-factorial designs utilize different participant groups to avoid carryover effects. The optimal choice hinges on the specific research context and the potential for confounding variables. Both designs are valuable tools in psychological research, each offering unique advantages and disadvantages.
Answer Length
This is a comprehensive model answer for learning purposes and may exceed the word limit. In the exam, always adhere to the prescribed word count.