Predict Conditional Effects

Description

Predicts conditional treatment effects based on a fitted EffectLiteR model.

Usage

elrPredict(obj, newdata = NULL)

Arguments

Value

Object of class "data.frame".

Examples

m1 <- effectLite(y="dv", z=c("z1"), k=c("k1","kateg2"), x="x", 
control="control", data=example01)
newdata <- data.frame(k1="male", kateg2="1", z1=2)
elrPredict(m1, newdata)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EffectLiteR)
Loading required package: lavaan
This is lavaan 0.5-20
lavaan is BETA software! Please report any bugs.
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EffectLiteR/elrPredict.Rd_%03d_medium.png", width=480, height=480)
> ### Name: elrPredict
> ### Title: Predict Conditional Effects
> ### Aliases: elrPredict
> 
> ### ** Examples
> 
> m1 <- effectLite(y="dv", z=c("z1"), k=c("k1","kateg2"), x="x", 
+ control="control", data=example01)
> newdata <- data.frame(k1="male", kateg2="1", z1=2)
> elrPredict(m1, newdata)
           g1     se_g1         g2     se_g2   Eygx0kz    Eygx1kz     Eygx2kz
1 -0.09468854 0.2482164 -0.2439777 0.2400799 0.1850225 0.09033393 -0.05895525
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>