ident_Y_type

This function identifies the outcome's type according to the model
if the user does not directly specify it.
The type of outcome could be <code>'ordinal'</code> or any other characters, e.g., 'non-ordinal'.
This is an internal function, automatically called by the function <code>FormalEstmed</code>.

This program realizes a universal estimation approach that accommodates
multi-category variables and effect scales, making up for the deficiencies
of the existing approaches when dealing with non-binary exposures and
complex models. The estimation via bootstrapping can simultaneously provide results of
causal mediation on risk difference (RD), odds ratio (OR) and risk ratio (RR) scales with tests of the effects' difference.
The estimation is also applicable to many other settings, e.g., moderated mediation, inconsistent covariates,
panel data, etc. The high flexibility and compatibility
make it possible to apply for any type of model, greatly meeting the needs of
current empirical researches.

Tianbao Zhou

unvs.med

A Universal Approach for Causal Mediation Analysis

Xinghao Li

Lin Liu*

ident_Y_type function

<dl><dt>Y</dt>
<dd>a character variable of the outcome's name.</dd>
<dt>data</dt>
<dd>a dataframe used in the analysis.</dd></dl>

Arguments

Identification of Outcome's type — ident_Y_type

<dl>

<dt>Y</dt>
<dd>a character variable of the outcome's name.</dd>


<dt>data</dt>
<dd>a dataframe used in the analysis.</dd>

</dl>

ident_Y_type: Identification of Outcome's type

Description

Usage

Value

Arguments