For my Master's thesis, I have to establish a model and test it with (moderated) regression analysis. My supervisor told me that regression analysis can help me resolve my research question but I can't figure out how.
I notices there 5 more or less recent posts on moderation in regression but somehow I receive the messege "The requested topic does not exist" when I click on any one of them. Also, I think my question might go a bit beyond.
In my initial model, I have two independent variables - goals and pay - and one dependent variable - performance. Hypothesis 1 (goals are positively related to performance) and hypotheses 2 (rewards are positively related to performance) are supported.
In the second step, I introduce a set of possible moderators. Because I am going to test for each of them separately, I will now just look at one, uncertainty. I suggest that uncertainty moderates both main effects. The effect of goals (and rewards, respectively) on performance is greater if uncertainty is low than if uncertainty is high. I intend to test it with SPSS with two hierarchical regression analyses. In the first level, I introduce goals (and rewards, respectively) and uncertainty as independent variables, in the second level I add the interaction term, with the interaction term goals x uncertainty in the first regression, and the interaction term rewards x uncertainty in the second regression. As far as I understand, moderation would be supported by a significant change in the variance explained (R squared) after adding the interaction term.
(performance = a + b*goals + c*uncertainty + d*goals x uncertainty + e; performance = a + b*rewards + c*uncertainty + d*rewards x uncertainty + e)
Problem: Now, my supervisor wants me to find out when goals are enough to get performance and when rewards are (additionally) necessary. I can't find a way to put it more clearly and also cannot make a hypotheses out of it. I have no idea how I can test for this effect. Maybe you could understand the question by looking at the conclusion it should give. A possible conclusion could be: When uncertainty is low, goals lead to performance (even in the absence of rewards or independent of rewards); however, if uncertainty is high, goals only lead to performance if combined with rewards.
I am sorry that my explanation turned out a bit long. I tried to make it as clear as possible.
I'd be really happy if someone could help me solve my problem. Any suggestions are welcome. Please let me know if you need any addional info or clarification.