bmem.em.boot {bmem}

Bootstrap for EM

Description

Bootstrap for EM

Usage

bmem.em.boot(x, ram, indirect, v, robust = FALSE, 
             varphi = 0.1, st= "i", boot = 1000, 
             moment = FALSE, max_it = 500, ...)

Arguments

x

A data set

ram

RAM path for the mediaiton model

indirect

A vector of indirect effec

v

Indices of variables used in the mediation model. If omitted, all variables are used.

robust

Roubst method

varphi

Percent of data to be downweighted

st

Starting values

boot

Number of bootstraps. Default is 1000.

moment

Select mean structure or covariance analysis. moment=FALSE, covariance analysis. moment=TRUE, mean and covariance analysis.

max_it

Maximum number of iterations in EM

...

Other options for sem function can be used.

Details

The indirect effect can be specified using equations such as a*b, a*b+c, and a*b*c+d*e+f. A vector of indirect effects can be used indirect=c('a*b', 'a*b+c').

Value

par.boot

Parameter estimates from bootstrap samples

par0

Parameter estimates from the orignal samples

Author(s)

Zhiyong Zhang and Lijuan Wang