Child Care and Early Education Research Connections

Skip to main content

Examining the foundations of methods that assess treatment effect heterogeneity across intermediate outcomes

Share
Description:
The goal of this study is to better understand how methods for estimating treatment effects of latent groups operate. In particular, we identify where violations of assumptions can lead to biased estimates, and explore how covariates can be critical in the estimation process. For each set of approaches, we first review the assumptions necessary for identification and discuss practical issues that arise in estimation. We then examine how covariates allow for improved estimation, and determine the conditions necessary for using covariates to identify causal effects in latent groups. We then compare the different methods using simulation studies built from datasets constructed by imputing missing class membership and potential outcomes from real-world studies. This allows for examining the performance of the different techniques under a variety of plausible circumstances. We finally apply these methods to two common data sets that represent the type of data increasingly available to researchers, the JOBS II study and the Head Start Impact Study (HSIS), and compare the resulting treatment effect estimates to each other and some plausible baseline values. (author abstract)
Resource Type:
Reports & Papers
Country:
United States

- You May Also Like

These resources share similarities with the current selection.

Preparing centers and a literacy-rich environment for small-group instruction in Early Reading First preschools

Other

Evaluation: Practical applications for closing achievement gaps

Other

Why families should matter for Early Reading First

Other

Assessing and creating effective preschool literacy classroom environments

Other
Release: 'v1.24.0' | Built: 2023-01-23 14:56:35 EST