Dear R users,
my question concerns my interest in comparing the beta coefficients between two identical regression models in two (actually 3) groups. Disclaimer: I am quite new to R, so I might be missing some terminology that I have not come across. I am trying to find out if I can easily implement a Wald test in R for this, but the only relevant thing that I came across is this link (http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/aod/html/wald.test.html), which seems to be referring to comparing the coefficients of separate IVs within the same regression. What I am interested is to compare the coefficients of the same IVs across three regressions and across three groups. Some basic information about my model/design: My model includes 2 fixed factors (task, group) and 5 more IVs of interest. Choice ~ Task * Group + IV1 + IV2 + IV3 + IV4 + IV5 I established that the Task * Group interaction is significant (by running two models of a regression, one comparing a model with and one without the interaction term) and I am interested to explore group differences within each task in a separate logistic regression. Task has 3 levels, therefore I do 3 of the following regressions: Choice ~ Group + IV1 + IV2 + IV3 + IV4 + IV5, one for each level of Task. At this point I want to compare betas for the 5 IVs across my 3 groups (actually I don't even need to compare all 5, based on the theory behind it, if that is a concern for some in terms of groupwise errors). PS: I did a z-test across my critical IVs between groups, which is quite similar to Wald. I just want to do the Wald as well to doublecheck my results. PS2: I also did another thing that some people might suggest, which is to recode Group in 2 dummy variables and include those and the interaction terms within each of my 3 regressions. I could go one step back and do it in the original regression (Choice ~ Task * Group + IV1 + IV2 + IV3) but I want to avoid having to include the complicated 3-way interactions. Also, I don't think it is much of a problem to analyze different tasks individually, especially after I have already established that the Task * Group interaction is significant. So, can someone provide the code or point me to a place that a similar issue might already have been discussed, for the case of doing a Wald test to compare the beta coefficients of specific IVs of interest between different regressions/groups (same model used for all thesegroups)? Thanks in advance, Kostas [[alternative HTML version deleted]]
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