# Testing interaction terms individually and simultaneously

I am currently testing two interaction terms individually in OLS regressions. Both interaction terms are significant (p < .5) when tested individually (i.e., two regression equations, one for each interaction term) but both interaction terms become insignificant (p > .1) when tested at the same time (i.e., two interaction terms in a single regression equation). The correlation between my two moderators is moderate ($$r = 0.44$$). What might be some possible reasons for the terms becoming insignificant when tested simultaneously?

• Can you clarify what you mean by simultaneous testing? What are the p-values in each case? – Bryan Krause May 6 at 16:08
• Thanks. I tried to make it more clear. – user18075 May 6 at 16:26
• Could you be more specific about how you are "testing at the same time"? Are you consulting the individual p-values or are you perhaps examining the F statistic for the two interactions together? – whuber May 6 at 16:43
• Re the edit: this is an example of a phenomenon discussed in many good posts. See the hits at stats.stackexchange.com/…. – whuber May 6 at 17:06
• Sorry if it is still confusing. When I test both interaction terms in a single regression equation both interaction terms become insignificant (p > .1). – user18075 May 6 at 17:07