causalmpt: Causal Mplus Trees

In MplusTrees: Decision Trees with Structural Equation Models Fit in 'Mplus'

Causal Mplus Trees

Description

Uses Mplus Trees to match on structural equation model parameters in matching subsample. Then estimates Conditional Average Treatment Effects (CATEs) in holdout estimation subsample.

Usage

causalmpt(
  script,
  data,
  rPartFormula,
  group = ~id,
  treat,
  outcome,
  est.samp = 0.2,
  ...
)

Arguments

script	An MplusAutomation script file
data	Dataset that is specified in the script
rPartFormula	Formula of the form ~ variable names
group	id variable. If not specified an id variable is created for each row
treat	Treatment variable
outcome	Univariate outcome of interest (dependent variable in mean comparison tests)
est.samp	Proportion of sample to be used as holdout sample (estimation subsample)
...	Other arguments to MplusTrees for building Mplus Tree

Details

See documentation for MplusTrees() for further information on tree building process. Takes terminal nodes from Mplus Tree and considers them "matched". Splits estimation subsample into groups defined by covariate pattern in terminal nodes from Mplus Tree. Performs t tests in each group with treat as independent variable and outcome as dependent variable to estimate CATEs. Also performs ANOVA to determine if treatment effect differs by group (interaction).

Value

An object of class 'causalmpt'. Tree structure drawn from MplusTrees(). CATEs estimated in estimation (holdout) subsample. Provides results of t tests to estimate CATEs in each group and ANOVA to examine group differences in treatment effect.

Author(s)

Sarfaraz Serang

References

Serang, S., & Sears, J. (2021). Tree-based matching on structural equation model parameters. Behavioral Data Science, 1, 31-53.

Examples

## Not run: 
library(lavaan)

script = mplusObject(
   TITLE = "Causal Mplus Trees Example",
   MODEL = "f1 BY x1-x3;",
   usevariables = c('x1','x2','x3'),
   rdata = HolzingerSwineford1939)

fit.cmpt = causalmpt(script, HolzingerSwineford1939, group=~id,
   rPartFormula=~school+grade,
   control=rpart.control(minsplit=100, minbucket=100, cp=.01),
   treat="sex", outcome="x4")
fit.cmpt

## End(Not run)

MplusTrees documentation built on Oct. 11, 2022, 5:07 p.m.