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Fixed or random effects meta-analysis? Common methodological issues in systematic reviews of effectiveness
Abstract
Systematic review aims to systematically identify, critically appraise, and summarize all relevant studies that match predefined criteria and answer predefined questions. The most common type of systematic review is that assessing the effectiveness of an intervention or therapy. In this article, we discuss some of the common methodological issues that arise when conducting systematic reviews and meta-analyses of effectiveness data, including issues related to study designs, meta-analysis, and the use and interpretation of effect sizes.
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“Additionally, it was recommended that the protocol should define the methods to be used for risk of bias assessment, meta-analysis and exploration of heterogeneity [41, 42, 44].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [44]
In the citing paper
“The articles recommended that the protocol should state the objectives, hypotheses to be tested and the rationale of the review, [29] and that it should describe eligibility criteria [29, 33, 35, 36, 38, 39, 41], define the type of studies to be included [35, 37, 42, 44], and give the reason when including observational studies in the review [35, 37, 40].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [44]
In the citing paper
“Twenty-five (27%) articles gave recommendations on item “considering different study designs” [8, 29, 34, 35, 37–39, 42, 44, 49, 51, 56, 61, 65, 70, 73, 75, 76, 77–83], with publication dates between 1995 and 2016 (median year of publication 2007).”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [44]
In the citing paper
“A variation of this recommendation was to exclude studies that are at high risk of bias [42, 44, 54, 73, 82].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [44]
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“For data analysis, we used the classical random effects method [55].”
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“Considering the clinical and methodological heterogeneity, we based our analysis on the random-effects model of decision-making selection by Tufanaru et al. [20].”
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“In view of the variability in assessment tools (generating heterogeneity) and because results were intended to be generalized beyond the included studies, random-effects models were conducted (Tufanaru et al., 2015).”
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“Heterogeneity was considered unimportant with I 2 = 0–30%; moderate, I 2 = 40–50%; substantial I 2 = 60–75% and considerable I 2 ≥ 75% [29].”
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Wang, K., Xia, G.-M., Liu, Y.-H., Jiao, S.-R., Gao, Y., & Deng, S. (2026) · Pathogens · doi:10.3390/pathogens15070767 · Cited by 2
“A random-effects model was applied when I 2 was ≥ 50%, indicating statistically significant heterogeneity [24]; otherwise, a fixed-effects model was selected [25].”
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van der Haak, N., Wood, K., Sweeney, A., & Munn, Z. (2018) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003451 · Cited by 2
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Impact of aquatic exercise on persons with kidney disease: a systematic review and meta-analysis
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“Statistical analyses will be performed using random or fixed effects models as described by Tufa-naru et al. 25 Where statistical pooling is not possible, the findings will be presented in narrative format, with tables and figures to aid in data presentation, where appropriate.”
MethodChaudhari, P. K., Dhingra, K., Dhillon, H., Zere, E., Sharan, J., Kumar, A., Alam, M. K., & Marya, A. (2022) · JBI Evidence Synthesis · doi:10.11124/jbies-21-00345 · Cited by 2
Kantor, J., Li, J., Du, J., Svobodová, Z., Klugar, M., Salehi‐Pourmehr, H., Hampton, D. D., Smolíková, M., Kantorová, L., Marečková, J., et al. (2023) · JBI Evidence Synthesis · doi:10.11124/jbies-22-00251 · Cited by 5
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“Statistical analyses will be performed using a random effect model [22].”
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“Unless the number of studies is small, a random-effect approach provides a useful starting point (e.g., Dettori et al., 2022; Tufanaru et al., 2015).”
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Effect of Tele-exercise Interventions on Quality of Life in Cancer Patients: A Meta-analysis
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“Adjusted point estimates were pooled using the generic inverse variance method under the fixed-effect model [21].”
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“Following Tufanaru et al, 36 a random-effects model was employed as the default to generalize conclusions beyond the included studies and made results more conservative.”
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“Random effects models were applied in all analyses regardless of heterogeneity, as evidence suggests more robust outcome measures compared to the fixed-effects models [12].”
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“A random-effects model was applied as it does not assume that there is a single true underlying effect and weighs studies more equally if there is heterogeneity (Basu, 2017; Tufanaru et al., 2015).”
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Patel, K., & Hoover, K. W. (2017) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2016-003186 · Cited by 2
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Bennett, C. L., Rebafka, A., Carrier, J., Edwards, D. J., & Jones, J. (2018) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003478 · Cited by 2
“2015.(43) Where statistical pooling is not possible the findings will be presented in narrative form including tables and figures to aid in data presentation where appropriate A funnel plot will be generated to assess publication bias if there are 10 or more studies included in a meta-analysis.”
BackgroundMethodInfluentialPreen, C., Munn, Z., Raju, S. E., & Flack, N. (2018) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003505 · Cited by 2
Self-citationKourbelis, C., Franzon, J., Foote, J. W., Brown, A. D. H., Daniel, M., Coffee, N. T., Newman, P., Nicholls, S. J., & Clark, R. A. (2018) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003543 · Cited by 2
Stewart, T., Reilly, R. E., & Ward, J. S. (2018) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003504 · Cited by 2
Smith, J. A., Secombe, P. J., & Aromataris, E. (2019) · JBI Evidence Synthesis · doi:10.11124/jbisrir-d-19-00196 · Cited by 2
Self-citationCarrier, S. L., Hicks, A. J., Ponsford, J. L., & McKay, A. (2020) · JBI Evidence Synthesis · doi:10.11124/jbies-20-00216 · Cited by 2
Lopes, R. O. P., Barbosa, G. D. S., Zaccaro, K. R. L., Mercês, C. A. M. F., Santana, R. F., & Brandão, M. A. G. (2020) · JBI Evidence Synthesis · doi:10.11124/jbisrir-d-19-00295 · Cited by 2
Organic food consumption and the incidence of cancer: a systematic review protocol
Jadotte, Y. T., Koos, J. A., & Lane, D. S. (2020) · JBI Evidence Synthesis · doi:10.11124/jbies-20-00115 · Cited by 2
“Data synthesis Data from experimental and observational studies will be meta-analyzed separately.(18) The random effects model accounts for the between-study variability and is the preferred meta-analytic approach in this review.”
MethodFerszt, P., Hill, J., & Larson, S. L. (2020) · JBI Evidence Synthesis · doi:10.11124/jbies-20-00141 · Cited by 2
Remington, J., & Winters, K. P. (2017) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2016-003307 · Cited by 2
Hochheim, M., Ramm, P., & Amelung, V. E. (2022) · PLoS ONE · doi:10.1371/journal.pone.0273983 · Cited by 2
“This model not only accounts for the statistical heterogeneity of the included studies, but allows for generalisation beyond these studies [52,53].”
MethodSmith, A., Weigand, J., Greenwood, J., & Tierney, K. (2022) · JBI Evidence Synthesis · doi:10.11124/jbies-21-00476 · Cited by 2
Macdonald, M., Weeks, L. E., Moody, E., Martin‐Misener, R., Iduye, D., States, C., Ignaczak, M., Delahunty‐Pike, A., Caruso, J., Simm, J., et al. (2022) · JBI Evidence Synthesis · doi:10.11124/jbies-21-00409 · Cited by 2
Hawke, L. D., Brown, E. E., Rodak, T., Rossell, S. L., Ski, C. F., Strudwick, G., Thompson, D. R., Wang, W., Xu, D., & Castle, D. J. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-063846 · Cited by 3
Datta, P. K., Aravindan, A., Nath, S., Chowdhury, S. R., & Dutta, D. (2023) · Lung India · doi:10.4103/lungindia.lungindia_473_22 · Cited by 2
“Fixed-effect model was used to meta-analyse the data in case a number of studies was 5 or less.[7] In case studies used different pulmonary function parameters to assess expiratory flow function, such as forced expiratory volume in 1 second (FEV1) or peak expiratory flow rate (PEFR), sensitivity analysis was done for…”
MethodRahim, U. A., Roos, N. A. C., Mustapa, M., Nurdin, A., Taridi, N. M., & Yusof, Y. A. M. (2023) · Advances in Human Biology · doi:10.4103/aihb.aihb_222_22 · Cited by 2
Kumar, S., Nayak, S., Kanagokar, V., & Pitchaimuthu, A. N. (2024) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2024.2316293 · Cited by 2
“…the best model to estimate the overall effect is often selected based on the number of studies and the degree of heterogeneity. tufanaru et al. [41] recommended a fixed effects (Fe) model when the number of studies is less than five and the heterogeneity is low (i 2 < 30%). if the above-stated…”
Dennis, R., Christian, R., & Palokas, M. J. (2019) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003926 · Cited by 2
“2015.(29) Subgroup analyses will be conducted where there is sufficient data to investigate patient diagnosis, length of time on LAI antipsychotic medications, age and sex.”
BackgroundMori, E., Iwata, H., Maehara, K., Sakajo, A., Ina, K., & Harada, N. (2019) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003974 · Cited by 2
Hines, S. J., Carey, T. A., Martin, K., & Cibich, M. (2019) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-d-19-00041 · Cited by 2
Arvig, M. D., Laursen, C. B., Jacobsen, N., Gæde, P., & Lassen, A. T. (2019) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-d-19-00027 · Cited by 2
de Barros, K. A. A. L., Martins, M. A. P., Praxedes, M. F. D. S., & Ribeiro, A. L. P. (2021) · JBI Evidence Synthesis · doi:10.11124/jbies-20-00399 · Cited by 2
Fuge, T. G., Tsourtos, G., & Miller, E. R. (2022) · Research Square · doi:10.21203/rs.3.rs-840708/v1 · Cited by 2
Kim, R., Kang, N., Lee, T. L., Lee, H., Ko, D. K., Lee, J. H., Shin, H., Lim, D., Jun, J., Byun, K., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3162661/v1 · Cited by 2
George, S., Barrett, M., Ionno, J. D., Fletcher, L., Choo, W. S., Rivas-Dominguez, S., Romanic, N., Lizarondo, L. M., & Stern, C. (2021) · JBI Evidence Synthesis · doi:10.11124/jbies-20-00407 · Cited by 1
Vanier, C. H., Johnston, K., DeArmond, M., Salloum, L., Arjmand, S., Toder, E., & Ioudina, M. (2022) · JBI Evidence Synthesis · doi:10.11124/jbies-21-00378 · Cited by 1
Yoon, J.-H., Kim, E. H., Park, S. B., Jin, H., & Yoon, S. W. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1125373 · Cited by 1
“In other cases, a random effects model was used (Tufanaru et al., 2015).”
MethodAutism Spectrum Disorder and Face Identity Recognition Deficit across Ages
Song, Y. (2023) · Graduate Student Journal of Psychology · doi:10.52214/gsjp.v20i1.10622 · Cited by 1
Ahmad, M. A., Awar, S. A. A. R. A., Sallam, G. S., Alkaabi, M. S. N., Smetanina, D., Statsenko, Y. A., & Zaręba, K. T. (2024) · Healthcare · doi:10.3390/healthcare12060650 · Cited by 5
“Specifically, we plan to apply a random effects model, which helps to generalise findings beyond the included papers [52].”
MethodKownaklai, J., Phanwichatkul, T., Chaichan, A., & Lee, A. J. (2024) · Pacific Rim International Journal of Nursing Research · doi:10.60099/prijnr.2024.264145 · Cited by 1
Endodontic Surgery and Post-Treatment Apical Periodontitis: A Systematic Review
Iqbal, A., Khattak, O., Almutairi, H. A., Almaktoom, I. T., Alanazi, G. R. A., Alruwaili, K. H. A., Alruwaili, A. M., Alftaikhah, S. A. A., Issrani, R., Mustafa, M., et al. (2024) · The Open Dentistry Journal · doi:10.2174/0118742106296829240513095047 · Cited by 1
Metadata
- Authors
- Tufanaru, C., Munn, Z., Stephenson, M., & Aromataris, E.
- Affiliations
- The University of Adelaide (AU)
- Venue
- International Journal of Evidence-Based Healthcare
- Published
- 2015-09
- Volume
- 13
- Issue
- 3
- Pages
- 196-207
- ISSN
- 1744-1595 (ISSN-L)
- 1744-1609
- OpenAlex
- W2180006680
- Cited by
- 1,057
- References
- 62
- Citations by year
- 2026: 77 · 2025: 151 · 2024: 204 · 2023: 167 · 2022: 157 · 2021: 101 · 2020: 65 · 2019: 57 · 2018: 48 · 2017: 22 · 2016: 8
- FWCI
- 4.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Evidence-Based Healthcare (publishedVersion)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Keywords
- fixed-effects meta-analysis, random-effects meta-analysis, systematic review methodology, intervention effectiveness, effect size, research design
- MeSH terms
- Humans, Research Design, Review Literature as Topic, Meta-Analysis as Topic, Odds Ratio, Guidelines as Topic, Cross-Over Studies, Evidence-Based Medicine, Observational Studies as Topic
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