extract.modmed.mlm {multilevelmediation}

Post-processing of a model fit with modmed.mlm

Description

Post-processing of a model fit with modmed.mlm

Usage

extract.modmed.mlm(
  fit,
  type = c("all", "fixef", "recov", "recov.vec", "indirect", "a", "b", "cprime", "covab",
    "indirect.diff", "a.diff", "b.diff", "cprime.diff"),
  modval1 = NULL,
  modval2 = NULL
)

Arguments

fit

Result of modmed.mlm.

type

Character indicating which piece of information to extract from the model "all": fixed effects and var-cov matrix of random effects, as a single vector. "fixef": just fixed effects. "recov": var-cov matrix of random effects, as a matrix. "recov.vec": var-cov matrix of random effects, as a stacked vector. "indirect": value of the indirect effect. "a": Current value of a path. "b": Current value of b path. "cprime": Current value of c path. "covab": Random effect covariance between a and b paths, if both paths have associated random effects. "indirect.diff": difference in indirect effect at two values of the moderator (set by modval1 and modval2). "a.diff": difference in a at two values of the moderator (set by modval1 and modval2). "b.diff": difference in b at two values of the moderator (set by modval1 and modval2). "cprime.diff": difference cprime at two values of the moderator (set by modval1 and modval2).

modval1

If enabled, other quantities such as the indirect effect, a, b, and cprime, will be computed at this particular value of the moderator. Otherwise, value of these quantities is directly extracted from the model output (i.e., these would represent values of the effects when the moderator = 0).

modval2

Second value of the moderator at which to compute the indirect effect.

Details

This function extracts relevant parameter estimates from models estimated using modmed.mlm. For any of the .diff values, these are always the value of the effect at modval1 minus modval2.

Value

A vector or single numeric value corresponding to the parameter estimate(s) of interest is returned.

Examples

# Example data for 1-1-1 w/o moderation
data(BPG06dat)

# Fit model
fit<-modmed.mlm(BPG06dat,"id", "x", "y", "m",
  random.a=TRUE, random.b=TRUE, random.cprime=TRUE)
extract.modmed.mlm(fit, type="indirect")