Using the Two-Way ANOVA test in Research
This easy tutorial will show you how to run the Two Way ANOVA test in SPSS, and how to interpret the result.
The two-way ANOVA is a parametric test. In other words, We use two-way ANOVA, if we want to determine whether there is an interaction effect between two independent variables (factors) on the dependent variable. However, we may also determine whether there is the main effect of each factor on the dependent variable.
Moreover, the two-way analysis of variance is an extension of the one-way analysis of variance. However, because implementing the two-way ANOVA is relatively complicated, some clinical researchers prefer to apply the one-way ANOVA for one factor on each level of the other factor, repeatedly. (Source)
Assumptions of the Two-Way ANOVA Test
When performing a Two-Way ANOVA procedure the following assumptions are required
- The populations from which the samples were obtained must be normally or approximately normally distributed.
- The samples must be independent.
- The variances of the populations must be equal.
- The groups must have the same sample size.
- One continuous dependent variable
- two categorical independent variables with two or more groups
An Example: Two-Way ANOVA Test
This guide will explain, step by step, how to run the Two way ANOVA test in SPSS statistical software by using an example.
We collected data on gender, marital status, and level of happiness from 94 participants. Moreover, we want to determine whether there is an interaction effect between gender and marital status on the level of happiness. Therefore, we have one continuous dependent variable and two independent categorical variables:
gender with two groups (male, female) and marital status with five groups (single, married, divorced, separated, widowed).
There is not an interaction effect between two independent variables (factors) on the dependent variable.
There is an interaction effect between two independent variables (factors) on the dependent variable.
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