Hello!
I apologise in advance if I missed it, but I couldn't find an answer in previous threads.
I run a generalized linear model with 1 factor (gender) and 5 covariates. No single variable appears to have a predictive value on my VD. However, when I test for interactions, many seem to have a significant effect.
First thing I thought is that probably a single variable has not enough predictive power over the VD, but it does when is combined with other(s).
Does this make sense? Theoretically, I can find an explanation to this, but how should I report it? «Individually, variables had no predictive effect on the VD but when considering the combined effect, they did»?
Thank you so much in advance =)
I apologise in advance if I missed it, but I couldn't find an answer in previous threads.
I run a generalized linear model with 1 factor (gender) and 5 covariates. No single variable appears to have a predictive value on my VD. However, when I test for interactions, many seem to have a significant effect.
First thing I thought is that probably a single variable has not enough predictive power over the VD, but it does when is combined with other(s).
Does this make sense? Theoretically, I can find an explanation to this, but how should I report it? «Individually, variables had no predictive effect on the VD but when considering the combined effect, they did»?
Thank you so much in advance =)