Each independent variable and the dependent variable generates mean scores through behavioral health surveys. We are comparing the independent variables effects on the dependent variable between high and low risk groups. So for example we would want to know if stress and pain predict higher depression scores among people at high risk vs. people at low risk.
Thank you Paul, but does this also take into consideration that we want to know the difference in prediction between high and low risk groups? Would we need to use a dummy variable for high and low risk groups in the regression?
Thanks again Paul. Would we also need to take interaction into consideration? For example if our three independent variables were stress, pain, and resilience, would we need to look at the interaction say between stress*high risk group to know more about how the high risk group stress predicts depression?
Thank you Paul. Just trying to make sure I understand and not sure that I was clear. My actual hypothesis is:
"Lower levels of optimism and resilience and higher levels of depression among high risk women will predict lower levels of maternal role attainment compared to low risk women"
If I only use the dummy variable for high-risk vs. low risk, it seems that I am only predicting that risk level predicts maternal role attainment. But really what I want to know is do low levels of optimism and resilience and higher levels of postpartum depression among high risk women predict low maternal role attainment? Would the interaction term take care of answering that question?
- Badges
- Science topic
- Similar topics
- Data Mining
- Classification