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Unifying Design-based Inference: A New Variance Estimation Principle

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abstract

This paper presents two novel classes of variance estimators with superior properties, in the absence of parametric or semi-parametricassumptions. The first new class of estimator is the Oblozene Chlebizky (OC) variance estimators as a novel alternative to the generalized sandwich in Paper 1 of 4. That the OC concept is unlikely to arise from other, more standard, frameworks is manifestly true in light of the 40 year lacuna since White (1980). For any member of the generalized sandwich variance estimator class, there is an OC with the same expected value. The this alternative replaces a random matrix at the center with a nonrandom one. The second type of estimator is guaranteed conservative for the variance of the estimator and is based upon a similar principle of replacing a random matrix with its expectation.

fields

stat.ME 1

years

2025 1

verdicts

ACCEPT 1

representative citing papers

On the Foundations of the Design-Based Approach

stat.ME · 2025-05-15 · accept · novelty 6.0

NURVA, a weaker replacement for SUTVA, supports within-experiment estimates but cannot support causal claims about interventions not actually assigned in the study.

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  • On the Foundations of the Design-Based Approach stat.ME · 2025-05-15 · accept · none · ref 2021 · internal anchor

    NURVA, a weaker replacement for SUTVA, supports within-experiment estimates but cannot support causal claims about interventions not actually assigned in the study.