A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis
Abstract Background Network meta-analysis (NMA) is a statistical method used to combine results from several clinical trials and simultaneously compare multiple treatments using direct and indirect evidence. Statistical heterogeneity is a characteristic describing the variability in the intervention...
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| Format: | Article |
| Language: | English |
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BMC
2021-12-01
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| Series: | Systematic Reviews |
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| Online Access: | https://doi.org/10.1186/s13643-021-01859-3 |
| _version_ | 1818459355681390592 |
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| author | Dapeng Hu Chong Wang Annette M. O’Connor |
| author_facet | Dapeng Hu Chong Wang Annette M. O’Connor |
| author_sort | Dapeng Hu |
| collection | DOAJ |
| description | Abstract Background Network meta-analysis (NMA) is a statistical method used to combine results from several clinical trials and simultaneously compare multiple treatments using direct and indirect evidence. Statistical heterogeneity is a characteristic describing the variability in the intervention effects being evaluated in the different studies in network meta-analysis. One approach to dealing with statistical heterogeneity is to perform a random effects network meta-analysis that incorporates a between-study variance into the statistical model. A common assumption in the random effects model for network meta-analysis is the homogeneity of between-study variance across all interventions. However, there are applications of NMA where the single between-study assumption is potentially incorrect and instead the model should incorporate more than one between-study variances. Methods In this paper, we develop an approach to testing the homogeneity of between-study variance assumption based on a likelihood ratio test. A simulation study was conducted to assess the type I error and power of the proposed test. This method is then applied to a network meta-analysis of antibiotic treatments for Bovine respiratory disease (BRD). Results The type I error rate was well controlled in the Monte Carlo simulation. We found statistical evidence (p value = 0.052) against the homogeneous between-study variance assumption in the network meta-analysis BRD. The point estimate and confidence interval of relative effect sizes are strongly influenced by this assumption. Conclusions Since homogeneous between-study variance assumption is a strong assumption, it is crucial to test the validity of this assumption before conducting a network meta-analysis. Here we propose and validate a method for testing this single between-study variance assumption which is widely used for many NMA. |
| first_indexed | 2024-12-14T23:13:02Z |
| format | Article |
| id | doaj.art-a2107014acd14119b8d6ae3c022c6219 |
| institution | Directory Open Access Journal |
| issn | 2046-4053 |
| language | English |
| last_indexed | 2024-12-14T23:13:02Z |
| publishDate | 2021-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Systematic Reviews |
| spelling | doaj.art-a2107014acd14119b8d6ae3c022c62192022-12-21T22:44:10ZengBMCSystematic Reviews2046-40532021-12-011011810.1186/s13643-021-01859-3A likelihood ratio test for the homogeneity of between-study variance in network meta-analysisDapeng Hu0Chong Wang1Annette M. O’Connor2Department of Statistics, College of Liberal Arts and Sciences, Iowa State UniversityDepartment of Statistics, College of Liberal Arts and Sciences, Iowa State UniversityDepartment of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State UniversityAbstract Background Network meta-analysis (NMA) is a statistical method used to combine results from several clinical trials and simultaneously compare multiple treatments using direct and indirect evidence. Statistical heterogeneity is a characteristic describing the variability in the intervention effects being evaluated in the different studies in network meta-analysis. One approach to dealing with statistical heterogeneity is to perform a random effects network meta-analysis that incorporates a between-study variance into the statistical model. A common assumption in the random effects model for network meta-analysis is the homogeneity of between-study variance across all interventions. However, there are applications of NMA where the single between-study assumption is potentially incorrect and instead the model should incorporate more than one between-study variances. Methods In this paper, we develop an approach to testing the homogeneity of between-study variance assumption based on a likelihood ratio test. A simulation study was conducted to assess the type I error and power of the proposed test. This method is then applied to a network meta-analysis of antibiotic treatments for Bovine respiratory disease (BRD). Results The type I error rate was well controlled in the Monte Carlo simulation. We found statistical evidence (p value = 0.052) against the homogeneous between-study variance assumption in the network meta-analysis BRD. The point estimate and confidence interval of relative effect sizes are strongly influenced by this assumption. Conclusions Since homogeneous between-study variance assumption is a strong assumption, it is crucial to test the validity of this assumption before conducting a network meta-analysis. Here we propose and validate a method for testing this single between-study variance assumption which is widely used for many NMA.https://doi.org/10.1186/s13643-021-01859-3HeterogeneityBetween-study varianceNetwork meta-analysisHypothesis testing |
| spellingShingle | Dapeng Hu Chong Wang Annette M. O’Connor A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis Systematic Reviews Heterogeneity Between-study variance Network meta-analysis Hypothesis testing |
| title | A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis |
| title_full | A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis |
| title_fullStr | A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis |
| title_full_unstemmed | A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis |
| title_short | A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis |
| title_sort | likelihood ratio test for the homogeneity of between study variance in network meta analysis |
| topic | Heterogeneity Between-study variance Network meta-analysis Hypothesis testing |
| url | https://doi.org/10.1186/s13643-021-01859-3 |
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