Literature DB >> 20442194

Estimation of dose-response functions for longitudinal data using the generalised propensity score.

Erica E M Moodie1, David A Stephens.   

Abstract

In a longitudinal study of dose-response, it is often necessary to adjust for confounding or non-compliance, which may otherwise compromise the estimation of the true effect of a treatment. Using an approach based on the generalised propensity score (GPS)--a generalisation of the classical, binary treatment propensity score--it is possible to construct a balancing score that provides an estimation procedure for the true (unconfounded) direct effect of dose on response. Previously, the GPS has been applied only in a single interval setting; in this article, we extend the GPS methodology to the longitudinal setting to estimate the direct effect of a continuous dose on a longitudinal response. The methodology is applied to two simulated examples, and a real longitudinal dose-response investigation, the Monitored Occlusion Treatment of Amblyopia Study (MOTAS). In the treatment of childhood amblyopia, a common ophthalmological condition, occlusion therapy (patching) was for many decades the standard medical treatment, despite the fact that its efficacy was not quantified. MOTAS was revolutionary, as it was the first study to obtain precise measurements of the amount of occlusion each study participant received over the course of the study.

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Year:  2010        PMID: 20442194     DOI: 10.1177/0962280209340213

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  5 in total

1.  Using Directed Acyclic Graphs to detect limitations of traditional regression in longitudinal studies.

Authors:  Erica E M Moodie; D A Stephens
Journal:  Int J Public Health       Date:  2010-09-14       Impact factor: 3.380

2.  Neural Networks to Estimate Generalized Propensity Scores for Continuous Treatment Doses.

Authors:  Zachary K Collier; Walter L Leite; Allison Karpyn
Journal:  Eval Rev       Date:  2021-03-03

3.  The Association between Dietary Vitamin A and Carotenes and the Risk of Primary Liver Cancer: A Case-Control Study.

Authors:  Qiu-Ye Lan; Yao-Jun Zhang; Gong-Cheng Liao; Rui-Fen Zhou; Zhong-Guo Zhou; Yu-Ming Chen; Hui-Lian Zhu
Journal:  Nutrients       Date:  2016-10-11       Impact factor: 5.717

4.  Covariate association eliminating weights: a unified weighting framework for causal effect estimation.

Authors:  Sean Yiu; Li Su
Journal:  Biometrika       Date:  2018-09-03       Impact factor: 2.445

5.  Formulating causal questions and principled statistical answers.

Authors:  Els Goetghebeur; Saskia le Cessie; Bianca De Stavola; Erica Em Moodie; Ingeborg Waernbaum
Journal:  Stat Med       Date:  2020-09-23       Impact factor: 2.497

  5 in total

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