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Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling

BACKGROUND: Quasi-experimental studies of menu labeling have found mixed results for improving diet. Differences between experimental groups can hinder interpretation. Propensity scores are an increasingly common method to improve covariate balance, but multiple methods exist and the improvements as...

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Autores principales: Mayne, Stephanie L., Lee, Brian K., Auchincloss, Amy H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682980/
https://www.ncbi.nlm.nih.gov/pubmed/26677849
http://dx.doi.org/10.1371/journal.pone.0144962
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author Mayne, Stephanie L.
Lee, Brian K.
Auchincloss, Amy H.
author_facet Mayne, Stephanie L.
Lee, Brian K.
Auchincloss, Amy H.
author_sort Mayne, Stephanie L.
collection PubMed
description BACKGROUND: Quasi-experimental studies of menu labeling have found mixed results for improving diet. Differences between experimental groups can hinder interpretation. Propensity scores are an increasingly common method to improve covariate balance, but multiple methods exist and the improvements associated with each method have rarely been compared. In this re-analysis of the impact of menu labeling, we compare multiple propensity score methods to determine which methods optimize balance between experimental groups. METHODS: Study participants included adult customers who visited full-service restaurants with menu labeling (treatment) and without (control). We compared the balance between treatment groups obtained by four propensity score methods: 1) 1:1 nearest neighbor matching (NN), 2) augmented 1:1 NN (using caliper of 0.2 and an exact match on an imbalanced covariate), 3) full matching, and 4) inverse probability weighting (IPW). We then evaluated the treatment effect on differences in nutrients purchased across the different methods. RESULTS: 1:1 NN resulted in worse balance than the original unmatched sample (average standardized absolute mean distance [ASAM]: 0.185 compared to 0.171). Augmented 1:1 NN improved balance (ASAM: 0.038) but resulted in a large reduction in sample size. Full matching and IPW improved balance over the unmatched sample without a reduction in sample size (ASAM: 0.049 and 0.031, respectively). Menu labeling was associated with decreased calories, fat, sodium and carbohydrates in the unmatched analysis. Results were qualitatively similar in the propensity score matched/weighted models. CONCLUSIONS: While propensity scores offer an increasingly popular tool to improve causal inference, choosing the correct method can be challenging. Our results emphasize the benefit of examining multiple methods to ensure results are consistent, and considering approaches beyond the most popular method of 1:1 NN matching.
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spelling pubmed-46829802015-12-31 Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling Mayne, Stephanie L. Lee, Brian K. Auchincloss, Amy H. PLoS One Research Article BACKGROUND: Quasi-experimental studies of menu labeling have found mixed results for improving diet. Differences between experimental groups can hinder interpretation. Propensity scores are an increasingly common method to improve covariate balance, but multiple methods exist and the improvements associated with each method have rarely been compared. In this re-analysis of the impact of menu labeling, we compare multiple propensity score methods to determine which methods optimize balance between experimental groups. METHODS: Study participants included adult customers who visited full-service restaurants with menu labeling (treatment) and without (control). We compared the balance between treatment groups obtained by four propensity score methods: 1) 1:1 nearest neighbor matching (NN), 2) augmented 1:1 NN (using caliper of 0.2 and an exact match on an imbalanced covariate), 3) full matching, and 4) inverse probability weighting (IPW). We then evaluated the treatment effect on differences in nutrients purchased across the different methods. RESULTS: 1:1 NN resulted in worse balance than the original unmatched sample (average standardized absolute mean distance [ASAM]: 0.185 compared to 0.171). Augmented 1:1 NN improved balance (ASAM: 0.038) but resulted in a large reduction in sample size. Full matching and IPW improved balance over the unmatched sample without a reduction in sample size (ASAM: 0.049 and 0.031, respectively). Menu labeling was associated with decreased calories, fat, sodium and carbohydrates in the unmatched analysis. Results were qualitatively similar in the propensity score matched/weighted models. CONCLUSIONS: While propensity scores offer an increasingly popular tool to improve causal inference, choosing the correct method can be challenging. Our results emphasize the benefit of examining multiple methods to ensure results are consistent, and considering approaches beyond the most popular method of 1:1 NN matching. Public Library of Science 2015-12-17 /pmc/articles/PMC4682980/ /pubmed/26677849 http://dx.doi.org/10.1371/journal.pone.0144962 Text en © 2015 Mayne et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Mayne, Stephanie L.
Lee, Brian K.
Auchincloss, Amy H.
Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title_full Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title_fullStr Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title_full_unstemmed Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title_short Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling
title_sort evaluating propensity score methods in a quasi-experimental study of the impact of menu-labeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682980/
https://www.ncbi.nlm.nih.gov/pubmed/26677849
http://dx.doi.org/10.1371/journal.pone.0144962
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