This mediation analysis regards how much of the social inequality (as a binary exposure) in long term sickness absence is mediated through physical work environment.
The mediator is the logarithm of the physical work environment score (between 1 and 100 with 100 corresponding to a physically very demanding work environment) at baseline.
In this example the authors Lange et al. they state:
We can now compute the first part of the weights by using the actual observed values for the mediator, the predicted means, and the residual standard deviation (manually taken from the output of PROC GENMOD, in combination with the probability density function for a normal distribution.
DATA newMyData; SET newMyData; weightDIR = PDF('normal',logphys, predM, 1.2083); RUN; DATA newMyData; SET newMyData; weightINDIR = PDF('normal',logphys, predMStar, 1.2083); RUN; DATA newMyData; SET newMyData; w = weightINDIR/weightDIR; RUN;
It's not very clear to me why they would use a normal distribution to generate direct and indirect weights?
Why is the final weight generated as the fraction of weights of direct and indirect effects?
Reference: Theis Lange, Stijn Vansteelandt, and Maarten Bekaert; A Simple Unified Approach for Estimating Natural Direct and Indirect Effects; American Journal of Epidemiology 2011.