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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...

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Autores principales: Wang, Li, Lewis-Beck, Colin, Fritschel, Elyse, Baser, Erdem, Baser, Onur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Columbia Data Analytics, LLC 2013
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.
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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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