Reply With QuoteThis address gives you almost all you need.
I have some problems I need help with. I am running a binary logistic regression.
DV: Brand choice (0/1)
IV1: Attitude towards product (p<0.05)
IV2: Price sensitivity (p<0.05)
I have found that “Attitude towards product” is more powerful (B=1.308) than “Price sensitivity” (B=0.956) in predicting brand choice. However, according to my thesis supervisor, in order to claim this fact, I need to run an additional test. That is, I need to find out if this difference is significant. I have been searching a lot, but I cannot find how I am supposed to test this. Does anybody have an ideas??
I have read that it is possible to run a t-test (with brand choice as grouping variable) and look at the t-values and if the t-value for “Attitude towards product” is higher, then it is the stronger one. However, I have 3 groups (conditions) so I’m not sure that I can run a t-test. Can I use an ANOVA instead and look at the F-values?
Would appreciate help! Thanks!
This address gives you almost all you need.
"victor is the reviewer from hell" -Jake
Thans for your help, but I can't reallt find the answer to my question in the address you posted. I have only one model whereas the link discusses comparisons between two models.
Yes I agree, but I think that conversation might apply to comparing the coefficients within one model or between different models.
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