predict.FindIt

object

An optional data frame in which to look for variables with which to predict.
                 If omitted, the data used in <code>FindIt</code> is used.

newdata

Whether to sort samples according to estimated treatment effects.

sort

When <code>sort=TRUE</code>, whether to sort samples in descending order or not.

decreasing

If <code>unique=TRUE</code>, <code>predict</code> returns unique samples.

unique

Further arguments passed to or from other methods.

<code>predict.FindIt</code> takes an output from <code>FindIt</code> and returns
  estimated treatment effects when <code>treat.type="single"</code> and
  predicted outcomes for each treatment combination when <code>treat.type="multiple"</code>.

FindIt implements the heterogeneous
        treatment effect estimation procedure proposed by Imai and
        Ratkovic (2013).  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.

predict.FindIt: Computing predicted values for each sample in the data.

Description

Usage

Arguments

Value

Details

Examples