I am trying to report the results of a study that employs a 2 (between subjects: tx vs ctrl) X 4 (within subject: time :T0,T1, T2 and T3) mixed factorial ANOVA. I have analyzed the data using both SPSS and JAMOVI.
Personally, I find the JAMOVI results cleaner and the graphs of estimated marginal means much better because SPSS is not graphing with error bars at all. and JAMOVI tables are much simpler.
Question is: why does SPSS provide a multivariate table here for an analysis that is essentially univariate (One continuous DV), then follows it up with separate tables for within and between subjects factors?
Second, from the JAMOVI output, I have been using the interaction term posthoc testing to breakdown the significant interaction- I wanted to verify this is essentially doing the same thing as a simple main effects analysis. conceptually this is testing each level of each factor within each level of the other factor- so this should be okay, right?
It is not true that SPSS cannot graph error bars. It is possible to show confidence intervals as well as standard errors. Maybe you use an old, outdated SPSS version?
ad 1) I think your description is not correct. The results from the multivariate table and the univariate tables should differ and you do NOT have ONE continous variable but 4, since you have 4 repeated measures. Using an ANOVA approach ist only one method to analyze repeated measures using difference scores. Another approach would be to use MANOVA, where your 4 repeated measures are considered as four DVs. Please have a look at Tabachnick & Fidell (2013) for a detailed description of this approach (a third option would be a multilevel model, which has been recommended instead of an ANOVA apporach in the last couple of years).
ad 2) Is the question if simple main effects are ok? Which post hoc analyzes are "okay" depends on your hypotheses and cannot be answered without further information.
Tabachnick, B. G., Fidell, L. S. (2013). Using multivariate statistics (7th ed.). Boston, MA: pearson.
Regarding the SPSS output:
Multivariate Table: SPSS initially presents a multivariate table because it's considering the multiple time points as separate dependent variables, providing a comprehensive overview of the analysis.
Separate Tables: The subsequent within- and between-subjects tables offer focused analyses for each type of factor, aiding interpretation.
Regarding JAMOVI output and post-hoc testing:
Interaction Term Post-Hoc Testing: Yes, this is conceptually similar to simple main effects analysis, as it examines the effects of one factor within each level of the other. It's an appropriate approach to break down significant interactions.
Additional considerations:
MANOVA vs. Repeated Measures ANOVA: While SPSS uses repeated measures ANOVA, JAMOVI's approach aligns with MANOVA, treating the multiple time points as dependent variables. Both are valid methods, but it's essential to understand the conceptual differences.
Error Bars in SPSS: Ensure you've enabled error bars in the SPSS graphing options. They are available and provide valuable insights into variability.
General Recommendations:
Choose the Software You're Comfortable With: Select the software that aligns best with your preferences and understanding.
Understand Analytical Approaches: Be familiar with the underlying concepts of repeated measures ANOVA and MANOVA to interpret results accurately.
Graphs and Tables: Utilize visual aids effectively to communicate findings clearly.
Report Essential Information: Include ANOVA tables, effect sizes, post-hoc results, and graphs in your report.
Clarity and Conciseness: Present results in a clear and understandable manner, emphasizing key findings and their implications.
This is what bard has to say for your query. Hope this helps.
Anuraj Nayarisseri is your whole answer generated by "bard"? At least the "JAMOVI MANOVA" approach is not correct!! JAMOVI does NOT use a MANOVA approach for repeated measures in the ANOVA dialogue. Moreover, to my knowledge there isn't even a MANOVA option implemented in JAMOVI, unless you call it directly via the R command window, manually.
If you compare the mixed ANOVA results from SPSS and JAMOVI, both show exactly the same results.
This is the problem with AI generated answers, superficially, they are correct, but the details are often wrong or at leasst misleading and therefore should not be used to answer highly specific questions, as asked in this forum, imho.
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