Get Help to Run MANOVA in SPSS

Multivariate Analysis of Variance (MANOVA) is a statistical procedure that determines whether there are any simultaneous differences in a set of dependent variables based on the independent variable. Whenever groups must be compared across multiple dependent variables, a multivariate statistical analysis is conducted, and the data should have an approximate normal distribution. Examples of multivariate statistical analysis include cluster analysis, MANOVA, and exploratory factor analysis. If you are seeking expert guidance with MANOVA analysis in SPSS, our professional data analysts assist you in unlocking deeper insights from your data using the advanced analytic features of the software. Additionally, this article is a comprehensive guide to how to run a MANOVA test in SPSS to gain meaningful insights, how to interpret the output, and an example for reference.

Types of MANOVA in Statistics

(1). One-way MANOVA

A one-way MANOVA is used to determine whether there are any differences between an independent group on one or more continuous variables. Below is a visual representation of this type of MANOVA:

(2). Two-way MANOVA

A two-way MANOVA allows for the simultaneous exploration of the effect of factor variables on multiple response variables. Below is a visual representation of the two-way MANOVA:

What Are MANOVA Assumptions?

1. Lack of outliers. Box plots and Mahalanobis distance can be checked for this.
2. There must be two or more dependent variables.
3. Dependent variables are multivariate and normally distributed within each group of the independent variables.
4. The variance-covariance matrices of each group of residuals are equal.
5. Residuals follow the multivariate-normal probability distribution with means equal to zero.

MANOVA vs ANOVA

Hire an Expert to Run MANOVA in SPSS From Our Company

Our expert statisticians offer customized solutions to deliver accurate and reliable insights. After statistical analysis, they interpret the SPSS output of the MANOVA analysis focusing on key elements that give insights into the effect of the independent variable on the group of dependent variables. This section provides a comprehensive overview of how to run a MANOVA in SPSS, how to interpret the output, and an example.

How to Run a MANOVA in SPSS

Step 1: Click on Analyze> General Linear Model> Multivariate

Click on the Analyze tab> General Linear Model> Multivariate on the main menu. A multivariate dialogue box will be presented. This box consists of four primary sections: 1. ) Dependent variables 2.) Fixed factors 3.) Covariates 4.) Weighted Least Squares (WLS) weight.

Step 2: Transfer the variables

Transfer the dependent variables into the Dependent Variables box and the independent variables to the Fixed Factors box using the appropriate buttons. This is done by using the drag-and-drop feature to position the variables into their respective boxes. Alternatively, a standard arrow button, the transfer arrow, can be used to transfer the variables from the list on the left and to the analysis box on the right.

Step 3: Click on the Options button

Click on the Options button, and you will be presented with the Multivariate: Options dialogue box. The key components of this dialogue box are: 1.) Descriptive statistics 2.) Estimates of effect size 3.) Observed power 4.) Parameter estimates 5.) SSCP matrices 6.) Residual SSCP matrix.

Step 4: Select the Descriptive Statistics Box

In the Display area, you will be presented with the Descriptive Statistics checkbox; click on it. This step is crucial to obtain summary statistics of the independent variables.

Step 5: Click on Continue

After selecting the Descriptive Statistics box, click on the Continue button that will return you to the Multivariate dialogue box. To generate output, click Ok.

How to Interpret MANOVA

Examine Multivariate Tests

The multivariate tests table gives four key statistics which are the Pillai’s trace, Wilks Lambda, Hotelling’s Trace, and Roy’s Largest Root. To determine the statistical significance of the analysis, check the “Sig.” column. If p<0.0005, then it translates to the independent variable being dependent on the dependent variable. If p>0.0005, then the independent variable is not dependent on the dependent variable. Below is an example of a multivariate test:

Table illustrating an example of a multivariate test table.

Descriptive statistics

The descriptive statistics table illustrates the mean and standard deviation of two different independent variables.

Table showing the descriptive statistics of MANOVA analysis

MANOVA Example

A professor wants to evaluate the impact of multiple teaching methods, online, physical, and hybrid, on three different subjects: Biology, English, and Mathematics. The dependent variables were the subjects scored in percentage by the students. They set up the data in SPSS with the teaching methods as the independent variable and the percentage scores as the dependent variable. They then checked the assumptions and ran the analysis in SPSS. The MANOVA analysis determined whether there was a statistically significant difference in the outcomes of implementing the teaching methods.

Summary

MANOVA is an analytical technique that expands upon the techniques of ANOVA to simultaneously evaluate the differences across multiple continuous dependent variables. It is categorized into two main types which are one-way MANOVA and two-way MANOVA. The former determines whether there is a difference between an independent group and one or more different groups. The latter allows for the simultaneous exploration of two independent variables on multiple variables. Our MANOVA analysis experts have extensive experience working with analysis software such as SPSS and conducting rigorous analyses to deliver accurate results. They offer personalized services specific to your request. Reach out to our expert statisticians today for help with data analysis. Request a free quote from our excellent customer service agents via our live chat today. You can also contact us to make any inquiries and you will get an almost immediate response from our team.