I struggling with some analysis I'm doing and would really appreciate some insights:
I'm measuring people's the dependency of "Environmental attitude" (DV) on number of hours of sports activities they are doing "out in the nature" (IV 1) and inside a building (IV 2) [the data is from a survey N~500). When I run a linear regression with these two I get that IV1 (nature hours) has positive significant effect on the DV, and IV2 does not.
Then I added another IV: the ratio between time the activities in the following form:
IV3 = ((time outside)-(time inside))/((time outside)+(time inside)) + 1
so it is a variable the ranges from 0 to 2, where 0 indicates only inside activities and 2 indicates only outside activities (and 1 is equal amount of time).
Obviously IV3 is highly correlated to IV1 and IV2. When I run a regression with the 3 of them, the R-square gets better (more of the variance is explained) but to my surprise IV2 (hours inside, which wasn't significant before) becomes significant as well as IV3 (the ratio) while IV1 becomes not-significant.
Why do you think that is happening? How would you approach this analysis?