The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Analysing Data and Undertaking Meta‐Analyses
Abstract
This chapter contains sections titled: Introduction Types of data and effect measures Study designs and identifying the unit of analysis Summarizing effects across studies Heterogeneity Investigating heterogeneity Sensitivity analyses Chapter information References
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“A total of 7 articles used auxiliary measures: 6 cohort studies [46–49,52–53] and 1 RCT [51].”
From Bright light therapy in the treatment of patients with bipolar disorder: A systematic review and meta-analysis (2020) · cites this paper as [51]
In the citing paper
“There was less heterogeneity between RCTs [44,45,50,51,54] (I2 = 20%, P = 0.29), so a random effects model was employed.”
From Bright light therapy in the treatment of patients with bipolar disorder: A systematic review and meta-analysis (2020) · cites this paper as [51]
In the citing paper
“Nine articles were include: 4 RCTs [44–45, 50–51] and 5 cohort studies [46–49, 55]”
From Bright light therapy in the treatment of patients with bipolar disorder: A systematic review and meta-analysis (2020) · cites this paper as [51]
In the citing paper
“Funnel plot asymmetry, involving 5 or more studies, was visually assessed due to biased results in statistical tests for prevalence outcomes in single-group studies (15,16).”
From Treatment Preferences in Patients With Hypothyroidism (2025) · cites this paper as [16]
In the citing paper
“Publication bias was assessed through visual inspection of a funnel plot graph on the primary outcome (post-treatment depression score) for asymmetry. This is an accepted approach, but is subject to inconsistency, with sufficient studies (≥10) being required to differentiate real from spurious asymmetry [20].”
From Behavioural Activation for Depression; An Update of Meta-Analysis of Effectiveness and Sub Group Analysis (2014) · cites this paper as [20]
Citations
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Self-citationA basic introduction to fixed-effect and random-effects models for meta-analysis
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Burger, R. J., van Eijk, A. M., Bussink, M., Hill, J., & ter Kuile, F. O. (2015) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofv170 · Cited by 28
Silva‐Neto, L. G. R., Neto, J. E. D. S., Bueno, N. B., de Oliveira, S. L., & Ataíde, T. D. R. (2018) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2018.1459469 · Cited by 27
Neuroprotection for treatment of glaucoma in adults
Sena, D. F., Ramchand, K. V., & Lindsley, K. B. (2010) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd006539.pub2 · Cited by 27
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Metadata
- Authors
- Deeks, J. J., Higgins, J. P., & Altman, D. G.
- Affiliations
- University of Birmingham (GB)
- MRC Biostatistics Unit (GB)
- University of Oxford (GB)
- Venue
- Cochrane Handbook for Systematic Reviews of Interventions
- Publisher
- Wiley
- Published
- 2008-09-22
- Pages
- 243-296
- OpenAlex
- W1596902544
- Cited by
- 1,800
- References
- 64
- Citations by year
- 2026: 31 · 2025: 73 · 2024: 70 · 2023: 82 · 2022: 90 · 2021: 228 · 2020: 149 · 2019: 118 · 2018: 89 · 2017: 88 · 2016: 115 · 2015: 102 · 2014: 115 · 2013: 108 · 2012: 96
- Type
- other
- Language
- en
- Open access
- closed
- 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
- meta-analysis, effect measures, research design, unit of analysis, heterogeneity, sensitivity analysis
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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