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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-citationStatistical Aspects of the Analysis of Data From Retrospective Studies of Disease
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Self-citationA basic introduction to fixed-effect and random-effects models for meta-analysis
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Blasco-Blasco, M., Castrejón, I., Jovaní, V., Pascual, E., & Ruiz‐Cantero, M. T. (2021) · The Journal of Rheumatology · doi:10.3899/jrheum.200967 · Cited by 21
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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
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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