Nonindependence and sensitivity analyses in ecological and evolutionary meta-analyses

Molecular Ecology

Volumn 26, Issue 9, 2017, Pages 2410-2425

  Noble, Daniel W A ^a   Lagisz, Malgorzata ^a   O’dea, Rose E ^a,b   Nakagawa, Shinichi ^a,b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b GARVAN INSTITUTE OF MEDICAL RESEARCH   (Australia)

Author keywords

Hierarchical structure; Meta analysis; Metaregression; Mixed models; Multilevel models; Quantitative research synthesis; Random effects

Indexed keywords

ECOLOGY; META ANALYSIS (TOPIC); METHODOLOGY; PHYLOGENY; PROCEDURES; UNCERTAINTY;

ECOLOGY; META-ANALYSIS AS TOPIC; PHYLOGENY; RESEARCH DESIGN; UNCERTAINTY;

EID: 85014420102     PISSN: 09621083     EISSN: 1365294X     Source Type: Journal    
DOI: 10.1111/mec.14031     Document Type: Article

References (64)

1. Aguilar R, Quesada M, Ashworth L, Herrerias-Diego Y, Lobo J (2008) Genetic consequences of habitat fragmentation in plant populations: susceptible signals in plant traits and methodological approaches. Molecular Ecology, 17, 5177–5188.
2. Adams D (2008) Phylogenetic meta-analysis. Evolution, 62–3, 567–572.
3. Aloe A (2015) Inaccuracy of regression results in replacing bivariate correlations. Research Synthesis Methods, 6, 21–27.
4. ArchMiller A, Bauer E, Koch R et al. (2015) Formalizing the definition of meta-analysis in molecular ecology. Molecular Ecology, 24, 4042–4051.
5. Besson A, Lagisz M, Senior A, Hector K, Nakagawa S (2016) Effect of maternal diet on offspring coping styles in rodents: a systematic review and meta-analysis. Biological Reviews, 91, 1065– 1080.
6. Bolker B, Brooks M, Clark C et al. (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology and Evolution, 24, 127–135.
7. Booksmythe I, Mautz B, Davis J, Nakagawa S, Jennions MD (2015) Facultative adjustment of the offspring sex ratio and male attractiveness: a systematic review and meta-analysis. Biological Reviews, 92, 108–134.
8. Borenstein M (2009) Effect size for continuous data. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 221–235. Russell Sage Foundation, New York.
9. Borenstein M, Hedges L, Higgens J, Rothstein H (2009) Introduction to Meta-Analysis. John Wiley & Sons Ltd, West Sussex, UK.
10. Chamberlain S, Hovick S, Dibble C et al. (2012) Does phylogeny matter? Assessing the impact of phylogenetic information in ecological meta-analysis. Ecology Letters, 15, 627–636.
11. Chapman JR, Nakagawa S, Coltman DW, Slate J, Sheldon BC (2009) A quantitative review of heterozygosity-fitness correlations in animal populations. Molecular Ecology, 18, 2746–2765.
12. Cheung MWL (2014) Modeling dependent effect sizes with threelevel meta-analyses: a structural equation modeling approach. Psychological Methods, 19, 211–229.
13. Cooper H, Hedges LV, Valentine JC (2009) The Handbook of Research Synthesis and Meta-analysis. Russell Sage Foundation, New York.
14. Dingemanse N, Dochtermann N, Nakagawa S (2012) Defining behavioural syndromes and the role of “syndrome deviation” in understanding their evolution. Behavioral Ecology and Sociobiology, 66, 1543–1548.
15. Dunlap W, Cortina JM, Vaslow J, Burke M (1996) Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods, 1, 170–177.
16. Forstmeier W, Wagenmakers E-J, Parker TH (2016) Detecting and avoiding likely false-positive findings—a practical guide. Biological Reviews. [Epub ahead of print]. doi:10.11111/brv.12315
17. Gates S (2002) Review of methodology of quantitative reviews using meta-analysis in ecology. Journal of Animal Ecology, 71, 547–557.
18. Gilbert K, Andrew R, Bock D, Franklin M (2012) Recommendations for utilizing and reporting population genetic analyses: the reproducibility of genetic clustering using the program structure. Molecular Ecology, 21, 4925–4930.
19. Gleser LJ, Olkin I (2009) Stochastically dependent effect sizes. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 357–376. Russell Sage Foundation, New York.
20. Greenhouse J, Iyengar S (2009) Sensitivity analysis and diagnostics. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 417–433. Russell Sage Foundation, New York.
21. Gurevitch J, Hedges L (1999) Statistical issues in ecological metaanalyses. Ecology, 80, 1142–1149.
22. Hadfield JD (2010) MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. Journal of Statistical Software, 33, 1–22.
23. Hadfield JD, Nakagawa S (2010) General quantitative genetic methods for comparative biology: phylogenies, taxonomies, and multi-trait models for continuous and categorical characters. Journal of Evolutionary Biology, 23, 494–508.
24. Hedges L (2007) Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32, 341–370.
25. Hedges L (2009a) Statistical consideration. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 38–46. Russell Sage Foundation, New York.
26. Hedges L (2009b) Effect sizes in nested designs. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 337–355. Russell Sage Foundation, New York.
27. Hedges LV, Gurevitch J, Curtis PS (1999) The meta-analysis of response ratios in experimental ecology. Ecology, 80, 1150–1156.
28. ST: how wrong have we been? Molecular Ecology, 18, 2080–2083.
29. Higgins J, Green S (2009) Cochrane Handbook for Systematic Reviews of Interventions. Wiley-Blackwell, Chichester, UK.
30. Hurlburt S (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs, 54, 187–211.
31. Isaksson C (2010) Pollution and its impact on wild animals: a meta-analysis on oxidative stress. EcoHealth, 7, 342–350.
32. Koricheva J, Gurevitch J (2014) Uses and misuses of meta-analysis in plant ecology. Journal of Ecology, 102, 828–844.
33. Koricheva J, Gurevitch J, Mengersen K (2013) Handbook of MetaAnalysis in Ecology and Evolution. Princeton University Press, Princeton, New Jersey.
34. Lajeunesse M (2009) Meta-analysis and the comparative phylogenetic method. The American Naturalist, 174, 369–381.
35. Lajeunesse M (2011) On the meta-analysis of response ratios for studies with correlated and multi-group designs. Ecology, 92, 2049–2055.
36. Liberati A, Altman D, Tetzlaff J et al. (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Medicine, 6, e1000100.
37. Marín-Martínez F, Sánchez-Meca J (1999) Averaging dependent effect sizes in meta-analysis: a cautionary note about procedures. The Spanish Journal of Psychology, 2, 32–38.
38. Mengersen K, Jennions M, Schmid C (2013) Statistical models for the meta-analysis of non-independent data. In: Handbook of MetaAnalysis in Ecology and Evolution (eds Koricheva J, Gurevitch J, Mengersen K), pp. 255–283. Princeton University Press, Princeton, New Jersey and Oxford.
39. Morrissey MB (2016) Meta-analysis of magnitudes, differences and variation in evolutionary parameters. Journal of Evolutionary Biology, 29, 1882–1904.
40. Nakagawa S, Cuthill IC (2007) Effect size, confidence interval and statistical significance: a practical guide for biologists. Biological Reviews, 82, 591–605.
41. Nakagawa S, Poulin R (2012) Meta-analytic insights into evolutionary ecology: an introduction and synthesis. Evolutionary Ecology, 26, 1085–1099.
42. Nakagawa S, Santos E (2012) Methodological issues and advances in biological meta-analysis. Evolutionary Ecology, 26, 1253–1274.
43. Nakagawa S, Schielzeth H (2010) Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biological Reviews, 85, 935–956.
44. Nakagawa S, Noble DWA, Senior AM, Lagisz M (2017) Meta-evaluation of meta-analysis: ten appraisal questions for biologists. BMC Biology, doi: 10.1186/s12915-017-0357-7.
45. Nekrutenko A, Taylor J (2012) Next-generation sequencing data interpretation: enhancing reproducibility and accessibility. Nature Reviews Genetics, 13, 667–672.
46. Osenberg C, Sarnelle O, Cooper S (1997) Effect size in ecological experiments: the application of biological models in meta-analysis. The American Naturalist, 150, 798–812.
47. Pinheiro J, Bates D (2000) Mixed-effects models in S and S-PLUS. Springer Verlag, New York.
48. van de Pol M, Wright J (2009) A simple method for distinguishing within-versus between-subject effects using mixed models. Animal Behaviour, 7, 753–758.
49. Poulin R (2000) Manipulation of host behaviour by parasites: a weakening paradigm. Proceedings of the Royal Society B: Biological Sciences, 267, 787–792.
50. Riley R, Price M, Jackson D et al. (2014) Multivariate meta-analysis using individual participant data. Research Synthesis Methods, 6, 157–174.
51. Roche D, Lanfear R, Binning S et al. (2014) Troubleshooting public data archiving: suggestions to increase participation. PLoS Biology, 12, e1001779.
52. Rothstein H, Sutton A, Borenstein M (2005) Publication bias in metaanalysis: Prevention, assessment and adjustments. Wiley, Chichester.
53. Rutkowska J, Dubiec A, Nakagawa S (2014) All eggs are made equal: a meta-analysis of egg sexual size dimorphism in birds. Journal of Evolutionary Biology, 27, 153–160.
54. Senior A, Grueber CE, Kamiya T et al. (2016) Heterogeneity in ecological and evolutionary meta-analyses: its magnitude and implications. Ecology, 97, 3293–3299.
55. Slate J, Phua H (2003) Patterns of linkage disequilibrium in mitochondrial DNA of 16 ruminant populations. Molecular Ecology, 12, 597–608.
56. Sutton A (2009) Publication bias. In: The Handbook of Research Synthesis and Meta-Analysis (eds Cooper H, Hedges LV, Valentine JC), pp. 435–452. Russell Sage Foundation, New York.
57. Thompson S, Higgins J (2002) How should meta-regression analysis be undertaken and interpreted? Statistics in Medicine, 21, 1559–1573.
58. Uller T, Nakagawa S, English S (2013) Weak evidence for anticipatory parental effects in plants and animals. Journal of Evolutionary Biology, 26, 2161–2170.
59. Verdu M, Traveset A (2005) Early emergence enhances plant fitness: a phylogenetically controlled meta-analysis. Ecology, 86, 1385–1394.
60. Vetter D, Rcker G, Storch I (2013) Meta-analysis: a need for welldefined usage in ecology and conservation biology. Ecosphere, 6, 1–24.
61. Viechtbauer W (2010) Conducting meta-analysis in R with the metafor package. Journal of Statistical Software, 36, 1–48.
62. Wallace BC, Lajeunesse MJ, Dietz G et al. (2016) openMEE: intuitive, open-source software for meta-analysis in ecology and evolutionary biology. Methods in Ecology and Evolution, doi: 10.1111/2041-210X.12708.
63. White T, Dalrymple R, Noble DWA et al. (2015) Reproducible research in the study of biological coloration. Animal Behaviour, 106, 51–57.
64. Worm B, Myers RA (2003) Meta-analysis of cod-shrimp interactions reveals top-down control in oceanic food webs. Ecology, 84, 162–173.