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Applied Comparison of Meta-analysis Techniques
Background: Meta-analysis is an approach that combines findings from similar studies. The aggregation of study level data can provide precise estimates for outcomes of interest, allow for unique treatment comparisons, and explain the differences arising from conflicting study results. Proper meta-an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Columbia Data Analytics, LLC
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471423/ https://www.ncbi.nlm.nih.gov/pubmed/37664148 http://dx.doi.org/10.36469/9848 |
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author | Wang, Li Lewis-Beck, Colin Fritschel, Elyse Baser, Erdem Baser, Onur |
author_facet | Wang, Li Lewis-Beck, Colin Fritschel, Elyse Baser, Erdem Baser, Onur |
author_sort | Wang, Li |
collection | PubMed |
description | Background: Meta-analysis is an approach that combines findings from similar studies. The aggregation of study level data can provide precise estimates for outcomes of interest, allow for unique treatment comparisons, and explain the differences arising from conflicting study results. Proper meta-analysis includes five basic steps: identify relevant studies; extract summary data from each paper; compute study effect sizes, perform statistical analysis; and interpret and report the results. Objectives: This study aims to review meta-analysis methods and their assumptions, apply various meta-techniques to empirical data, and compare the results from each method. Methods: Three different meta-analysis techniques were applied to a dataset looking at the effects of the bacille Calmette-Guerin (BCG) vaccine on tuberculosis (TB). First, a fixed-effects model was applied; then a random-effects model; and third meta-regression with study-level covariates were added to the model. Overall and stratified results, by geographic latitude were reported. Results: All three techniques showed a statistically significant effects from the vaccination. However, once covariates were added, efficacy diminished. Independent variables, such as the latitude of the location in which the study was performed, appeared to be partially driving the results. Conclusions: Meta-analysis is useful for drawing general conclusions from a variety of studies. However, proper study and model selection are important to ensure the correct interpretation of results. Basic meta-analysis models are fixed-effects, random-effects, and meta-regression. |
format | Online Article Text |
id | pubmed-10471423 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Columbia Data Analytics, LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-104714232023-09-01 Applied Comparison of Meta-analysis Techniques Wang, Li Lewis-Beck, Colin Fritschel, Elyse Baser, Erdem Baser, Onur J Health Econ Outcomes Res Respiratory Diseases Background: Meta-analysis is an approach that combines findings from similar studies. The aggregation of study level data can provide precise estimates for outcomes of interest, allow for unique treatment comparisons, and explain the differences arising from conflicting study results. Proper meta-analysis includes five basic steps: identify relevant studies; extract summary data from each paper; compute study effect sizes, perform statistical analysis; and interpret and report the results. Objectives: This study aims to review meta-analysis methods and their assumptions, apply various meta-techniques to empirical data, and compare the results from each method. Methods: Three different meta-analysis techniques were applied to a dataset looking at the effects of the bacille Calmette-Guerin (BCG) vaccine on tuberculosis (TB). First, a fixed-effects model was applied; then a random-effects model; and third meta-regression with study-level covariates were added to the model. Overall and stratified results, by geographic latitude were reported. Results: All three techniques showed a statistically significant effects from the vaccination. However, once covariates were added, efficacy diminished. Independent variables, such as the latitude of the location in which the study was performed, appeared to be partially driving the results. Conclusions: Meta-analysis is useful for drawing general conclusions from a variety of studies. However, proper study and model selection are important to ensure the correct interpretation of results. Basic meta-analysis models are fixed-effects, random-effects, and meta-regression. Columbia Data Analytics, LLC 2013-02-28 /pmc/articles/PMC10471423/ /pubmed/37664148 http://dx.doi.org/10.36469/9848 Text en https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (4.0) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Respiratory Diseases Wang, Li Lewis-Beck, Colin Fritschel, Elyse Baser, Erdem Baser, Onur Applied Comparison of Meta-analysis Techniques |
title | Applied Comparison of Meta-analysis Techniques |
title_full | Applied Comparison of Meta-analysis Techniques |
title_fullStr | Applied Comparison of Meta-analysis Techniques |
title_full_unstemmed | Applied Comparison of Meta-analysis Techniques |
title_short | Applied Comparison of Meta-analysis Techniques |
title_sort | applied comparison of meta-analysis techniques |
topic | Respiratory Diseases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471423/ https://www.ncbi.nlm.nih.gov/pubmed/37664148 http://dx.doi.org/10.36469/9848 |
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