Helper function to setup data and parameters for input to mvregmed.fit and mvregmed.grid
mvregmed.init(dat.obj, x.std = TRUE, med.std = TRUE, y.std = TRUE)A list of items used as input to model fitting.
A list that is output from mvregmed.dat.check that contains x, mediator, and y.
logical (TRUE/FALSE) whether to standardize x by dividing by standard devation of x. Note that each column of x will be centered on its mean.
logical (TRUE/FALSE) whether to standardize mediator by dividing by standard devation of mediator. Note that each column of mediator will be centered on its mean.
logical (TRUE/FALSE) whether to standardize y by dividing by standard devation of y. Note that each column of y will be centered on its mean.
Daniel Schaid and Jason Sinnwell
Center and scale (if declared) x, mediator and y. Then regress each mediator on all x to create residuals that are used to create the residual variance matrix for mediators. This variance matrix is penalized by glasso to obtain a matrix of full rank. Variance matrices for x and y variables are also created. Initial values of paramemeter matrices alpha, beta, and delta are created (all intital values = 0).
Schaid DS, Dikilitas O, Sinnwell JP, Kullo I (2022). Penalized mediation models for multivariate data. Genet Epidemiol 46:32-50.
mvregmed.fit
mvregmed.grid