Hello everyone,
I have a pressing question. I would like to investigate the way differences in average scores based on region, place of work (two groups) in interaction with anxiety scores affected sleep. My specific research question refers to the interaction between societal level factors (region of work), social (specific work variable) and individual (anxiety) would affect sleep.
I would like to better understand which method would be most suitable. I wanted to use ANOVA and investigate the interaction between region, place of work and anxiety scores (treating it as a five groups categorical variable), however when I try to do Levene test I recieve an error.
Another option would be to investigate the MLM-way. Having two level variables and looking into their effects in comparison to the individual level variable in its prediction.
Can somebody help me what method would be most suitable to use?
Thank you in advance!
All best, Nina
Cory Cobb Hey. Thank you for responding to my question. Yes, I was thinking of doing hierarchical linear modelling. Where I have the group averages at the cultural level (region), work group, individual level. Then I compare the interactions? What do you think? Or do you think just a simple multiple regression is ok?
Hi Nina, actually for your sample, I was talking about hierarchical regression rather than HLM, which is multilevel modeling. Many confuse HLM with hierarchical regression (although both are based in regression to a large degree). But you could just as easily use standard multiple regression and create interaction terms to include in the model.
Cory Cobb Thank you so much for explaining this to me! The standard multiple regression is much simpler and answers my question!
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