I am running a logistic regression, similar to the following:
Pr(Y = 1) = B0 + B1*X1 + B2*X2 + B3*X3 + e
X1 is an indicator variable. I find B1 is statistically insignificant. A colleague is worried that B1 may be insignificant because I have too few observations where X1 = 1 (about 0.50% of my sample of 10,000 observations). His suggestion is to randomly draw control observations to match the number of treatment observations and rerun the regression.
Alternatively, could I address this concern by simply bootstrapping my standard errors in my original regression and sample? Is bootstrapping a valid way to address power concerns?