Introduction
SPSS software is a tool to provide SPSS help with various data analysis techniques like ANOVA, T-test, Z-test, MANOVA, Chi-Square test, and much more. Most users prefer to use this tool because of its easy-to-handle interface and easy programming command language. By the topic, you must have gotten the idea that we are going to talk about MANOVA in this blog post.
MANOVA is actually employed when a user is testing multiple hypotheses concurrently and getting increased experiment error rates. Here we will discuss the definition of MANOVA, its benefits, how to perform this test on SPSS, and many more things. Read further to get a better clarity of the MANOVA test.
What is Multivariate Analysis of Variance (MANOVA)?
MANOVA is an extended form of ANOVA which has the ability to assess multiple dependent variables at the same time. ANOVA determines the difference between three or more group mean values, but it has a limitation. It cannot assess more than one dependent variable at a time and hence you might not detect the effects in some cases which actually exist. Even if you fit a general linear model with multiple independent variables, it will take only one dependent variable at a time to assess because it cannot determine the patterns through more than one dependent variable. This is the reason that in some cases, ANOVA cannot produce significant results. But, MANOVA can assess multiple dependent variables simultaneously and hence it has various advantages over ANOVA.
Comparison of MANOVA and ANOVA
The benefits of MANOVA
The MANOVA is preferably used when the dependent variables are correlated. This correlation between the variables provides some additional information to the model and hence MANOVA works with enhanced capabilities, which are as follows:
- In the case of correlated variables, MANOVA identifies even those effects which were undetected by the regular ANOVA test.
- The MANOVA can assess the different patterns established between multiple dependent variables.
- The MANOVA reduces the chances of neglecting the true null hypothesis and hence the error rate equals the significance level.
Steps to perform MANOVA using SPSS
- Enter your data in a between-subjects form.
- Click Analyse.
- Take your cursor to the “General Linear Model” drop-down menu & choose “Multivariate.”
- Highlight the first continuous outcome variable.
- Move the variable into the “Dependent Variable” box by clicking on “Arrow”.
- Repeat steps no. 4 and 5 until all the variables are in the “Dependent Variable” box.
- Move all the categorical predictor variables into the “Fixed factors” box by clicking on the “Arrow”.
- Click on “options”.
- Highlight the “Factor and Factor Interactions” box by clicking on the categorical predictor variable..
- Move the variable into the “Display means for” box by clicking on the “Arrow”.
- Select the “Compare main effects” box by clicking on it.
- Go to the “Display table” and click on the “Descriptive statistics”, “Estimates of effect size”, “Observed Power”, and “Homogeneity tests” boxes and select them.
- Click on “Continue” and then on “OK”.
Conclusion
Because of a single limitation of ANOVA, we use its extended version that it, MANOVA. It is also a statistical test which can deal with multiple dependent variables at the same time and hence enhances the performance of the ANOVA test. In the blog, we tried to explain MANOVA, its advantages over ANOVA, and how to use it on SPSS. If dealing with MANOVA SPSS still bothers you then you can take expert assistance. Good luck with analysing your data!
