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A scoping review of statistical methods for trial‐based economic evaluations: The current state of play
The statistical quality of trial‐based economic evaluations is often suboptimal, while a comprehensive overview of available statistical methods is lacking. Therefore, this review summarized and critically appraised available statistical methods for trial‐based economic evaluations. A literature sea...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826466/ https://www.ncbi.nlm.nih.gov/pubmed/36089775 http://dx.doi.org/10.1002/hec.4603 |
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author | El Alili, Mohamed van Dongen, Johanna M. Esser, Jonas L. Heymans, Martijn W. van Tulder, Maurits W. Bosmans, Judith E. |
author_facet | El Alili, Mohamed van Dongen, Johanna M. Esser, Jonas L. Heymans, Martijn W. van Tulder, Maurits W. Bosmans, Judith E. |
author_sort | El Alili, Mohamed |
collection | PubMed |
description | The statistical quality of trial‐based economic evaluations is often suboptimal, while a comprehensive overview of available statistical methods is lacking. Therefore, this review summarized and critically appraised available statistical methods for trial‐based economic evaluations. A literature search was performed to identify studies on statistical methods for dealing with baseline imbalances, skewed costs and/or effects, correlated costs and effects, clustered data, longitudinal data, missing data and censoring in trial‐based economic evaluations. Data was extracted on the statistical methods described, their advantages, disadvantages, relative performance and recommendations of the study. Sixty‐eight studies were included. Of them, 27 (40%) assessed methods for baseline imbalances, 39 (57%) assessed methods for skewed costs and/or effects, 27 (40%) assessed methods for correlated costs and effects, 18 (26%) assessed methods for clustered data, 7 (10%) assessed methods for longitudinal data, 26 (38%) assessed methods for missing data and 10 (15%) assessed methods for censoring. All identified methods were narratively described. This review provides a comprehensive overview of available statistical methods for dealing with the most common statistical complexities in trial‐based economic evaluations. Herewith, it can provide valuable input for researchers when deciding which statistical methods to use in a trial‐based economic evaluation. |
format | Online Article Text |
id | pubmed-9826466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98264662023-01-09 A scoping review of statistical methods for trial‐based economic evaluations: The current state of play El Alili, Mohamed van Dongen, Johanna M. Esser, Jonas L. Heymans, Martijn W. van Tulder, Maurits W. Bosmans, Judith E. Health Econ Research Articles The statistical quality of trial‐based economic evaluations is often suboptimal, while a comprehensive overview of available statistical methods is lacking. Therefore, this review summarized and critically appraised available statistical methods for trial‐based economic evaluations. A literature search was performed to identify studies on statistical methods for dealing with baseline imbalances, skewed costs and/or effects, correlated costs and effects, clustered data, longitudinal data, missing data and censoring in trial‐based economic evaluations. Data was extracted on the statistical methods described, their advantages, disadvantages, relative performance and recommendations of the study. Sixty‐eight studies were included. Of them, 27 (40%) assessed methods for baseline imbalances, 39 (57%) assessed methods for skewed costs and/or effects, 27 (40%) assessed methods for correlated costs and effects, 18 (26%) assessed methods for clustered data, 7 (10%) assessed methods for longitudinal data, 26 (38%) assessed methods for missing data and 10 (15%) assessed methods for censoring. All identified methods were narratively described. This review provides a comprehensive overview of available statistical methods for dealing with the most common statistical complexities in trial‐based economic evaluations. Herewith, it can provide valuable input for researchers when deciding which statistical methods to use in a trial‐based economic evaluation. John Wiley and Sons Inc. 2022-09-11 2022-12 /pmc/articles/PMC9826466/ /pubmed/36089775 http://dx.doi.org/10.1002/hec.4603 Text en © 2022 The Authors. Health Economics published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles El Alili, Mohamed van Dongen, Johanna M. Esser, Jonas L. Heymans, Martijn W. van Tulder, Maurits W. Bosmans, Judith E. A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title | A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title_full | A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title_fullStr | A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title_full_unstemmed | A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title_short | A scoping review of statistical methods for trial‐based economic evaluations: The current state of play |
title_sort | scoping review of statistical methods for trial‐based economic evaluations: the current state of play |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826466/ https://www.ncbi.nlm.nih.gov/pubmed/36089775 http://dx.doi.org/10.1002/hec.4603 |
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