theveryclosedcircle.blogspot/2012/04/360-meta-analysis.html

1. http://theveryclosedcircle.blogspot.com/2012/04/360-meta-analysis.htmlhttp://theveryclosedcircle.blogspot.com/2012/04/360-meta-analysis.html

2. Special Topics in Biological Data Analysis:Meta-analysis Jarrett Byrnes UMass Boston Spring 2014

3. Is one study ever definitive?

5. Tilman et al. 1997 Science Huston et al. 2000 Nature

6. How can we determine the answer?

7. Narrative Reviews • Author searches and summarizes evidence from their perspective • Can be biased by author’s own opinion or searching abilities (if they did a search)

8. “In a strictly defined sample of competition studies using controlled field experiments, covering 215 species and 527 experiments competition was found in most of the studies, in somewhat more than half of the species, and in about two-fifths of the experiments.” Connell 1983 “Rare until recently, field-experimental studies of interspecific competition now number well over 150. Competition was found in 90% of the studies and 76% of their species, indicating its pervasive importance in ecological systems.” Schoener 1983

9. Systematic Review • Defined repeatable criteria for searching • Clear inclusion/exclusion strategy • Systematic coding/grading of results from studies • Not often done outside of medicine • But see http://www.environmentalevidencejournal.org/ http://www.cochrane.org/ http://www.campbellcollaboration.org/

10. Vote-Counting • Says nothing about strength of effect • Weak evidence = no evidence, biased by experiments with large and small sample sizes “Rare until recently, field-experimental studies of interspecific competition now number well over 150. Competition was found in 90% of the studies and 76% of their species, indicating its pervasive importance in ecological systems.” Schoener 1983

12. One Giant P-Value • One study contains p(data|Hypothesis) for one data set • Why not combine them? For example: p=1-pnorm(Szi, m=0, s=1) • Unequal sample sizes, methodologies, assumptions, etc……

13. Meta-analysis! An analysis of analyses! Systematic combination of information from published studies to derive the weight of evidence to a particular question

14. The First Meta-Analysis Pearson, K. (1904). Report on certain enteric fever inoculation statistics. British Medical Journal, 3, 1243-1246.

15. 1970's: Dawn of Modern Meta-analysis • First, medical: Anti-coagulants as a treatment for heart attacks (Chalmers 1977) • Psychotherapy (Smith and Glass 1977) • Education: Class size and outcomes (Glass and Smith 1979) • Opposition: "an exercise in Mega-Silliness"

16. Why would you object to meta-analysis as a tool?

18. Characteristics of Meta-Analysis • Systematic search for studies • Strict criteria for inclusion • Common effect size • Analysis that accounts for difference in power of different studies Example: Hedge's D

21. Why did it take so long to get to Ecology? eigenfactor.org

22. Example 1: Strength of Competition Gurevitch et al. 1992

23. Example 2: Does Diversity Influence Ecosystem Function

24. Cardinale et al., Nature 2006 93 studies  175 experiments LRAve= ln(yp / ym) LRMax= ln(yp / ymax) Standing stock or Resource depletion Monoculture, m Most diverse polyculture, p Species richness

25. LRMax LRAve LRAve LRMax

26. Standing stock (YS / Ym) Resource depletion (YS / Ym)

27. Example 3: Are Seagrass Beds Changing? Waycott et al. 2009 PNAS

28. Example 3: Are Seagrass Beds Changing? Waycott et al. 2009 PNAS

29. For LOTS more in EEB • Ecology Volume 80 Issue 4 in 1999 • Ecology Volume 91 Issue 9 in 2010: Is meta-analysis a mega-mistake when it comes do diversity and productivity?

30. So what are we doing here?

31. Course Goals • Learn how to do a meta-analysis • DO a meta-analysis • and publish it! • Learn how to teach yourself new statistical skills • Learn how to participate in a working group type of environment

32. Course Outline • Now-March: Gathering and Assessing Data • March-April: Analytic Techniques • April-May: (not so) Unique Challenges

33. Class Structure • 1-2 or 2:15 You lecture on the topic of the week • 2:15-2:45 Code or other demo (if needed) • 2:45-4: Working group

34. I’m going to lecture?! • You will encounter many new analytic techniques in the future • This class provides an introduction to learning a new topic • Meet with me at 1pm on Tuesday to go over your lecture for the week • I’ll be lecturing on some of the hairy stuff & all of the code

35. a Requirement • We will use R for analysis • metafor package for meta-analysis • nlme and lmer for mixed models • MCMCglmm and JAGS for Bayesian methods http://www.metafor-project.org/

36. By March 1st! http://swirlstats.com/

37. http://www.nceas.ucsb.edu/handbook_of_meta-analysis

38. Other Books! • Introduction to Meta-Analysis. 2009. Michael Borenstein, Larry Hedges, Julian Higgins, and Hannah R. Rothstein. Wiley. • The Handbook of Research and Synthesis and Meta-Analysis, 2nd Edition. Edited by Harris Cooper, Larry Hedges, and Jeffry Valentine. Russel Sage Foundation.

39. What will you do in this course?

40. Choose a Question

41. Search the Literature, with a Protocol http://agris.fao.org/

42. (Re)Choose a Question

43. What will you do in this course?

44. Harvest Data http://arohatgi.info/WebPlotDigitizer/app/

45. Design a Database

46. Generate Strict Meta-data

47. Go back to the beginning… • As you begin to search, you will learn about what information is out there • Starting over (sometimes more than once) is normal!

48. Be Circumspect: Assess Bias, Power, Sensitivity, etc.

49. Analysis! http://www.metafor-project.org/

50. Publish?