I have been testing the association of particular gene sets with a disease (using the tool MAGMA https://doi.org/10.1371/journal.pcbi.1004219 ). In the output I get:
BETA: the regression coefficient of the variable BETA_STD: the semi-standardized regression coefficient, corresponding to the predicted change in Z-value given a change of one standard deviation in the predictor gene set / gene covariate (ie. BETA divided by the variable’s standard deviation) SE: the standard error of the regression coefficient P: p-value for the parameter / variable
I have some significant results from my analysis and I now want to know how strong of an effect those results have. I believe that Beta_STD is a standardized regression coefficient and therefore an effect size measure; however, I do not know what a good or bad value is for Beta_STD. My results with the lowest p-values also have the highest Beta_STD (~0.03) so yea. Thank you in advance!