I learned ANOVA and Regression are general linear model but they have some differences. then shouldn't it be different betweeen MANOVA and multivariate regression(multiple dependent variables)? when I look in to internet, there are only instructions about how to conduct MANOVA on SPSS. is it becuase MANOVA and multivariate regression is same or SPSS just doesn't provide multivariate regression?
which software is best for conducting multivariate regression?
If you use the GLM command (Analyze > General Linear Model > Multivariate) and include /PRINT=PARAMETER as an option, do you get what you want? For all /PRINT options, see the following pages in the documentation:
- https://www.ibm.com/docs/en/spss-statistics/30.0.0?topic=univariate-print-subcommand-glm-command#syn_glm_univariate_print
- https://www.ibm.com/docs/en/spss-statistics/30.0.0?topic=multivariate-print-subcommand-glm-command
You're right to question the distinction. While ANOVA and regression are related, their multivariate counterparts, MANOVA and multivariate regression, are distinct, though conceptually linked. They address slightly different research questions.
MANOVA: Tests for differences in multiple dependent variables between groups (categorical independent variable). Think of it as ANOVA but with several outcome measures.
Multivariate Regression: Predicts multiple dependent variables from one or more continuous or categorical independent variables. Think of it as regular regression but with several outcome measures.
SPSS does perform multivariate regression, though it might be less explicitly labeled. It's often done through the GLM (General Linear Model) procedure.
As for best software: SPSS, R, SAS, and JMP all handle multivariate regression. R is powerful and free, but has a steeper learning curve. SPSS is user-friendly but paid. The "best" depends on your needs and resources.
https://www.ibm.com/docs/sl/spss-statistics/beta?topic=statistics-multivariate-analysis-variance-manova@
Nuri Masoud Abduali I'd argue MANOVA doesn't test "... for differences in multiple dependent variables" or at least not in the sense that people think or that is generally useful.
MANOVA creates a weighted average of the various DVs and uses this as its DV. This weighting is opportunistic and atheoretical - its based on the optimal combination in the data (the weighted linear function of DVs that maximizes the variance). So if you repeated the study with new data for 4 DVS the second analysis using the same 4 DVs would have a different linear combination. This creates interpretability and other issues. Most researchers end up falling back on univariate analyses (incorrectly think the MANOVA has added adequate Type I error protection).
See https://psychologicalstatistics.blogspot.com/2021/08/i-will-not-ever-never-run-manova.html
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