Test2SRE: Hypothesis testing for three null hypotheses

In kosukeimai/RCT2: Designing and Analyzing Two-Stage Randomized Experiments

Hypothesis testing for three null hypotheses

Description

This function tests the null hypotheses of no direct effect, no marginal direct effect, and no spillover effect.

Usage

Test2SRE(data, effect = "DE", alpha = 0.05)

Arguments

data	A data frame containing the relevant variables. The names for the variables should be “Z” for the treatment assignment, “Y” for the treatment outcome, “A” for the treatment assignment mechanism, and “id” for the cluster ID. The variable for the cluster ID should be a factor.
effect	Specify which null hypothesis to be tested. “DE” for direct effect, “ME” for marginal effect, and “SE” for spillover effect.
alpha	The level of significance at which the test is to be run (default is 0.05).

Details

For the details of the method implemented by this function, see the references.

Value

A list of class Test2SRE which contains the following item:

rej	Rejection region for test conducted.

Author(s)

Kosuke Imai, Department of Statistics, Harvard University [e-mail], https://imai.fas.harvard.edu/; Zhichao Jiang, School of Public Health and Health Sciences, University of Massachusetts Amherst [e-mail]; Karissa Huang, Department of Statistics, Harvard College [e-mail]

References

Zhichao Jiang, Kosuke Imai (2020). “Statistical Inference and Power Analysis for Direct and Spillover Effects in Two-Stage Randomized Experiments”, Technical Report.

Examples

data(jd)
data_LTFC <- data.frame(jd$assigned, jd$pct0, jd$cdd6m, jd$anonale)
colnames(data_LTFC) <- c("Z", "A", "Y", "id")
Test2SRE(data_LTFC, effect="MDE", alpha=0.05)

kosukeimai/RCT2 documentation built on Oct. 27, 2022, 2:39 a.m.