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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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Constrained Design of a Binary Instrument in a Partially Linear Model.

Tim Morrison1, Minh Nguyen2, Jonathan Chen2

  • 1Statistics Stanford University.

Observational Studies
|May 11, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a two-stage method for optimal assignment of nudges in randomized encouragement designs to improve local average treatment effect (LATE) estimation. The approach offers a convex design criterion for efficient and constrained LATE estimation.

Keywords:
Design of experimentsInstrumental variablesPartially linear modelsRandomized controlled trialsRegression discontinuity

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Area of Science:

  • Econometrics
  • Causal Inference
  • Experimental Design

Background:

  • Randomized encouragement designs are used to estimate treatment effects when compliance is imperfect.
  • Assigning nudges effectively is crucial for accurate estimation of the local average treatment effect (LATE).
  • Existing methods may not be optimal for covariate-dependent nudge assignment.

Purpose of the Study:

  • To develop an optimal strategy for assigning nudges based on covariates in randomized encouragement studies.
  • To improve the estimation of the local average treatment effect (LATE) under a partially linear model.
  • To provide a flexible design criterion that accommodates practical constraints.

Main Methods:

  • A two-stage procedure is proposed for consistent and optimal LATE estimation.
  • A partially linear model is assumed, with a non-parametric baseline and linear treatment effect.
  • A finite sample approximation of the LATE variance is derived to create a convex design criterion for minimization.

    • Main Results:

    • The proposed two-stage method consistently and optimally estimates the LATE.
    • The derived design criterion is convex, allowing for incorporation of budgetary or ethical constraints.
    • The method demonstrated significant gains compared to a regression discontinuity design in a semi-synthetic emergency department triage example.

    Conclusions:

    • The developed two-stage procedure offers an optimal approach for nudge assignment in randomized encouragement studies.
    • The method provides a practical and efficient way to estimate LATE, even with constraints.
    • This approach shows promise for improving causal inference in observational and experimental settings.