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Main Author: Pashley, Nicole E.
Format: Preprint
Published: 2019
Subjects:
Online Access:https://arxiv.org/abs/1910.09062
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author Pashley, Nicole E.
author_facet Pashley, Nicole E.
contents The delta method creates more general inference results when coupled with central limit theorem results for the finite population. This opens up a range of new estimators for which we can find finite population asymptotic properties. We focus on the use of this method to derive asymptotic distributional results and variance expressions for causal estimators. We illustrate the use of the method by obtaining a finite population asymptotic distribution for a causal ratio estimator.
format Preprint
id arxiv_https___arxiv_org_abs_1910_09062
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
Pashley, Nicole E.
Methodology
The delta method creates more general inference results when coupled with central limit theorem results for the finite population. This opens up a range of new estimators for which we can find finite population asymptotic properties. We focus on the use of this method to derive asymptotic distributional results and variance expressions for causal estimators. We illustrate the use of the method by obtaining a finite population asymptotic distribution for a causal ratio estimator.
title Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
topic Methodology
url https://arxiv.org/abs/1910.09062