plot.PredictFindIt

output from <code>predict.FindIt</code>.

the argument specifying the main title of the plot.

main

the argument specifying the name of x axis.

xlab

the argument specifying the name of y axis.

ylab

whether to make a plot interactive; default is FALSE.

interactive

further arguments passed to or from other methods.

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Plot estimated treatment effects when <code>treat.type="single"</code> and
predicted outcomes for each treatment combination when
<code>treat.type="multiple"</code>.

The heterogeneous treatment effect estimation procedure
proposed by Imai and Ratkovic (2013)<DOI: 10.1214/12-AOAS593>.
The proposed method is applicable, for
example, when selecting a small number of most (or least)
efficacious treatments from a large number of alternative
treatments as well as when identifying subsets of the
population who benefit (or are harmed by) a treatment of
interest. The method adapts the Support Vector Machine
classifier by placing separate LASSO constraints over the
pre-treatment parameters and causal heterogeneity parameters of
interest. This allows for the qualitative distinction between
causal and other parameters, thereby making the variable
selection suitable for the exploration of causal heterogeneity.
The package also contains a class of functions, CausalANOVA,
which estimates the average marginal interaction effects (AMIEs)
by a regularized ANOVA as proposed by Egami and Imai (2019)<DOI:10.1080/01621459.2018.1476246>.
It contains a variety of regularization techniques to facilitate
analysis of large factorial experiments.

plot.PredictFindIt: Plot estimated treatment effects or predicted outcomes for each treatment combination.

Description

Usage

Arguments

Value

Details

Examples