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Introduction
Introduction
One-way ANOVA (link to Module page) is for analyzing data obtained from a study design with a single between-subjects factor with three or more levels.
There are other types of ANOVA for analyzing data from other study designs. Factorial ANOVA and repeated-measures ANOVA are two common types.
Generally, we use factorial ANOVA when our design has two or more factors, all between-subjects. For example, a 2 x 2 design has two between-subjects independent variables and each variable has two levels.
1. Factorial ANOVA
1. Factorial ANOVA
1.1 What is Factorial ANOVA?
1.1 What is Factorial ANOVA?
Sometimes we want to see how two or more independent variables work together in affecting the dependent variable. In particular, we can use factorial ANOVA to test interaction effect between two (or more) factors in influencing the DV. For example, suppose a new drug for treating depression was invented. Now, we want to test the effectiveness on human subjects. We have 2 conditions, the treatment group and no treatment group. Suppose we also want to see whether there is any gender difference. This design would contain 2 independent variables, drug condition with 2 levels {treatment vs no- treatment} and gender with 2 levels {female vs male}. Therefore, this study employs a 2x2 factorial design.
1.2 Example 1: Hostel, faculty, and sleeping hours
1.2 Example 1: Hostel, faculty, and sleeping hours
Suppose we had already found that there is a relationship between hostels and sleeping hours. Another group of researchers suggested that faculty is one of the major factors of number of sleeping hours, because workload may vary across faculties, which could have different effects on students' sleeping hours. Therefore, we consider hostel and faculty together and evaluate how they might interact in influencing sleeping hours.
Q: How do hostel and faculty (as IVs) influence sleeping hours (as DV)? Are there any main effects and/or interaction? (α = .05)
A: We used Factorial ANOVA to examine.
Step 1: Perform statistical analysis in jamovi (Please use full screen mode).
Example 8.1 FactorialANOVA_Sleep.mp4Based on the results from jamovi, we can draw the following conclusion.
Conclusion/ Interpretation (APA format):
There was a significant main effect of hostel, F(3, 188) = 3.29, p = .022, while the main effect of faculty was non-significant, F(2, 188) = 0.08, p = .924. However, the interaction effect was significant, F(6, 188) = 2.25, p = .004.
1.3 Example 2: Gender, relationship status, and SNS
1.3 Example 2: Gender, relationship status, and SNS
In daily life, we spend time on social networking sites (SNS) for communication and entertainment. It is believed that males and females are different in their SNS usage. In addition, relationship status can be one of the factors affecting the time on SNS. For instance, when a person is in a relationship, he/she may spend more time on SNS to interact with the partner. More specifically, such relationship-specific behavior could differ between males and females. Hence, we want to understand how the use of SNS is affected by gender and relationship status in a factorial design and test whether the gender X relationship interaction exists.
Q: How do gender and relationship status affect the use of SNS in hours? Are there any main effects and/or interaction? (α = .05)
A: We used Factorial ANOVA to examine.
Step 1: Perform statistical analysis in jamovi (Please use full screen mode).
Example 8.2 FactorialANOVA_SNS.mp4Based on the results from jamovi, we can draw the following conclusion.
Conclusion/ Interpretation (APA format):
The main effect of gender was non-significant, F(1, 194) = 0.01, p = .0920, and the main effect of relationship status was non-significant, F(2, 194) = 1.47, p = .232. Also, the interaction effect was non-significant, F(2, 194) = 0.20, p = .815.
Module Exercise (4% of total course assessment)
Module Exercise (4% of total course assessment)
Complete the exercise!
Complete the exercise!
Now, if you think you're ready for the exercise, you can check your email for the link.
Remember to submit your answers before the deadline in order to earn the credits!
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