Hope blow note will make things clear for you:

Mixed Factorial vs. Between-Subjects Experimental Design

Experimental designs are fundamental in research, as they dictate how data is collected and analyzed. Two commonly employed designs are mixed factorial designs and between-subjects designs, each suited to different research contexts based on the nature of the variables involved.

A mixed factorial design combines at least one between-subjects factor (where participants belong to different groups) and one within-subjects factor (where the same participants are exposed to multiple conditions). This design is particularly useful when researchers aim to study both group differences and changes over time or conditions.

In contrast, a between-subjects design involves testing all independent variables across separate groups of participants. Each participant is exposed to only one condition, ensuring no overlap in experiences and minimizing potential carryover or learning effects.

Mixed Factorial Design: Examples and Test Tools

For analyzing mixed factorial designs, the most common statistical test is mixed-design ANOVA, which evaluates main effects and interactions across both between-subjects and within-subjects factors.

Between-Subjects Design: Examples and Test Tools

Statistical tools for between-subjects designs include independent-samples t-tests for comparing two groups and one-way or two-way ANOVA for analyzing multiple groups or factors.

Conclusion

While both designs are invaluable in experimental research, their suitability depends on the research objectives. Mixed factorial designs are ideal for examining interactions and changes over time, while between-subjects designs are better for isolating the effects of independent variables. Selecting the appropriate design ensures meaningful and reliable results, paving the way for robust scientific insights.

This reply was got generated after discussions and inputs on research designed mentioned by you

Thank you so much, Rajendra K. Gupta. This note is very clear and it helps me a great deal in understanding these two important experimental designs.

you are welcome with more pointed doubts on your research design.