BootEstimation_for {unvs.med} | R Documentation |
Bootstrapping Estimation for Causal Mediation Effects via Ordinary "for" Loop
Description
This function obtains the estimates of mediation effects by the ordinary for
loop.
Through bootstrap sampling and repeating the algorithm of function SingleEstimation
,
This function obtains a number of estimates for each type of effect.
This is an internal function, automatically called by the function Statistics
.
Usage
BootEstimation_for (m_model, y_model, data, X, M, Y,
m_type, y_type, boot_num = 100)
Arguments
m_model |
a fitted model object for the mediator. |
y_model |
a fitted model object for the outcome. |
data |
a dataframe used in the analysis. |
X |
a character variable of the exposure's name. |
M |
a character variable of the mediator's name. |
Y |
a character variable of the outcome's name. |
m_type |
a character variable of the mediator's type. |
y_type |
a character variable of the outcome's type. |
boot_num |
the times of bootstrapping in the analysis. The default is 100. |
Details
This function is realized by the ordinary for
loop, therefore may take longer time to proceed.
For small amounts of data, e.g., dozens to a hundred samples, with relatively simple models,
for
loop is recommended.
Value
This function returns a list of three dataframes, i.e.,
the bootstrapping results of the mediation effects.
This list is also saved in the return of the main function FormalEstmed
.